OrthoEngine User's Guide.book
Geomatica OrthoEngine
User Guide
Geomatica Version 9.0, Release date: May, 2003
© 2003 PCI Geomatics Enterprises Inc.®. All rights reserved.
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Table of Contents
Chapter 1
USING ORTHOENGINE
Introducing Geomatica OrthoEngine ................................................................................................................................................................... 1
Getting Started .................................................................................................................................................................................................... 2
Working with OrthoEngine................................................................................................................................................................................... 2
How To Contact Us ............................................................................................................................................................................................. 4
Chapter 2
STARTING YOUR PROJECT AND SELECTING A MATH MODEL
Understanding the Math Models.......................................................................................................................................................................... 5
Understanding the Aerial Photography Math Model .................................................................................................................................... 5
Understanding Satellite Orbital Modelling.................................................................................................................................................... 5
Using the Right Math Model with IKONOS Data ......................................................................................................................................... 6
Understanding the Rational Functions Math Model..................................................................................................................................... 6
Understanding the Polynomial Math Model ................................................................................................................................................. 7
Understanding the Thin Plate Spline Math Model ....................................................................................................................................... 8
Starting OrthoEngine ........................................................................................................................................................................................... 9
Starting a Project Using the Aerial Photography Math Model ............................................................................................................................. 9
Starting a Project Using the Satellite Orbital Math Model.................................................................................................................................. 10
i
Starting a Project Using the Rational Functions Math Model............................................................................................................................. 11
Starting a Project Using the Polynomial Math Model ......................................................................................................................................... 11
Starting a Project Using the Thin Plate Spline Math Model ............................................................................................................................... 12
Starting a Project to Mosaic Existing Georeferenced Images............................................................................................................................ 12
Understanding Projections and Datums............................................................................................................................................................. 12
Setting the Projection ......................................................................................................................................................................................... 13
Chapter 3
IMPORTING AND VIEWING IMAGES
Importing Images or Photographs into Your Project .......................................................................................................................................... 15
Reading Satellite Images from a CD or a Digital Distribution Format ................................................................................................................ 15
Reading Satellite Data from a Tape ................................................................................................................................................................... 16
Reading Satellite Data from a Generic Image File............................................................................................................................................. 17
Importing Satellite Data from a PCIDSK File ..................................................................................................................................................... 17
Opening Images................................................................................................................................................................................................. 17
Supported Satellite Formats............................................................................................................................................................................... 18
Chapter 4
SETTING UP CAMERA CALIBRATION AND AERIAL PHOTOGRAPHS
Understanding Camera Calibration Data ........................................................................................................................................................... 21
Defining Focal Length ................................................................................................................................................................................ 21
Defining Principal Point Offset ................................................................................................................................................................... 22
Defining Radial Lens Distortion.................................................................................................................................................................. 22
Defining Decentering Distortion ................................................................................................................................................................. 22
Defining Photo Scale.................................................................................................................................................................................. 23
Defining Earth Radius ................................................................................................................................................................................ 23
Defining Fiducial Marks.............................................................................................................................................................................. 23
Defining Chip Size and Y Scale Factor ...................................................................................................................................................... 24
Entering the Camera Calibration Data ............................................................................................................................................................... 24
Collecting Fiducial Marks Manually.................................................................................................................................................................... 25
Collecting Fiducial Marks Automatically............................................................................................................................................................. 26
Understanding Exterior Orientation.................................................................................................................................................................... 26
Importing GPS/INS or Exterior Orientation Data from a Text File...................................................................................................................... 28
Entering the Exterior Orientation Manually ........................................................................................................................................................ 29
ii
Changing Photo Orientation .............................................................................................................................................................................. 30
Defining a Clip Region....................................................................................................................................................................................... 30
Chapter 5
COLLECTING CONTROL POINTS AND COMPUTING THE MATH MODELS
Understanding Ground Control Points............................................................................................................................................................... 33
Choosing Good Ground Control Points ..................................................................................................................................................... 34
Collecting the Right Number of Ground Control Points ............................................................................................................................. 34
Determining the Right Combination of Ground Control Points and Tie Points for the Satellite Math Model ..................................................... 35
Using Auto Locate ............................................................................................................................................................................................. 35
Using Bundle Update......................................................................................................................................................................................... 36
Collecting Ground Control Points Manually....................................................................................................................................................... 36
Collecting Ground Control Points from a Geocoded Image .............................................................................................................................. 37
Collecting Ground Control Points from Vectors................................................................................................................................................. 39
Collecting Ground Control Points from a Chip Database Manually................................................................................................................... 40
Searching for Chips in a Database ............................................................................................................................................................ 42
Working with the Chip Database ............................................................................................................................................................... 43
Collecting Ground Control Points from a Chip Database Automatically ............................................................................................................ 43
Changing the Correlation Parameters for Automatic GCP Collection from a Chip Database ................................................................... 44
Using a Tablet to Collect Ground Control Points............................................................................................................................................... 45
Setting Up the Tablet......................................................................................................................................................................................... 46
Collecting Ground Control Points from a Tablet ................................................................................................................................................ 47
Adding or Editing a Tablet ................................................................................................................................................................................. 48
Importing Ground Control Points from a File ..................................................................................................................................................... 49
Using a Digital Elevation Model to Set Ground Control Point Elevation............................................................................................................ 51
Understanding Tie Points .................................................................................................................................................................................. 51
Choosing Quality Tie Points ...................................................................................................................................................................... 52
Collecting Tie Points Manually .......................................................................................................................................................................... 52
Collecting Tie Points Automatically ................................................................................................................................................................... 53
Displaying the Overall Layout............................................................................................................................................................................ 54
Understanding the Bundle Adjustment for Rigorous Math Models.................................................................................................................... 55
Performing the Bundle Adjustment for Rigorous Math Models.......................................................................................................................... 55
Understanding the Solution for Simple Math Models ........................................................................................................................................ 56
Troubleshooting the Math Model Solution ......................................................................................................................................................... 56
Identifying Errors in the Math Model .......................................................................................................................................................... 57
iii
Generating a Residual Report............................................................................................................................................................................ 58
Editing Points in the Residual Report................................................................................................................................................................. 59
Defining the Tablet Format Strings .................................................................................................................................................................... 60
Chapter 6
GENERATING DIGITAL ELEVATION MODELS
Understanding Digital Elevation Models ............................................................................................................................................................ 63
Using Rasters to Generate a Digital Elevation Model ........................................................................................................................................ 64
Using Ground Control Points, Tie Points, and/or Elevation Match Points to Generate a Digital Elevation Model ............................................. 64
Using Vectors to Generate a Digital Elevation Model ........................................................................................................................................ 65
Generating the Digital Elevation Model from Rasters, Vectors, or Control Points ............................................................................................. 67
Understanding the Interpolation Methods for Vectors................................................................................................................................ 68
Building a Digital Elevation Model from a Stereo Pair of Images....................................................................................................................... 69
Creating Epipolar Images................................................................................................................................................................................... 69
Extracting Digital Elevation Models from Epipolar Pairs .................................................................................................................................... 71
Understanding Pixel Sampling and DEM Detail................................................................................................................................................. 73
Opening the Digital Elevation Model Editing Windows ...................................................................................................................................... 74
Switching Between the Image Channel and the DEM ....................................................................................................................................... 75
Editing the Digital Elevation Model..................................................................................................................................................................... 75
Creating a Mask ......................................................................................................................................................................................... 75
Replacing the Elevation Values Under a Mask .......................................................................................................................................... 76
Bulldozing a Line........................................................................................................................................................................................ 77
Filtering and Interpolating........................................................................................................................................................................... 77
Applying Tool Strategies for Common Situations in Digital Elevation Models ................................................................................................... 78
Equalizing Pixel Values for Lakes .............................................................................................................................................................. 78
Compensating for Forests and Urban Areas.............................................................................................................................................. 78
Neutralizing Cloud-Covered Areas............................................................................................................................................................. 79
Dealing with Noise ..................................................................................................................................................................................... 79
Geocoding a Digital Elevation Model ................................................................................................................................................................. 79
Exporting a Digital Elevation Model to a Text File.............................................................................................................................................. 80
Chapter 7
EDITING FEATURES IN 3-D STEREO
Understanding 3-D Stereo Viewing and Editing................................................................................................................................................. 81
iv
Viewing in 3-D Using Anaglyph Technology.............................................................................................................................................. 82
Viewing in 3-D Using OpenGL Technology ............................................................................................................................................... 82
Using Epipolar Images for 3-D Stereo Editing................................................................................................................................................... 82
Reducing Eyestrain ........................................................................................................................................................................................... 83
Examining the 3-D Feature Extraction Work Flow............................................................................................................................................. 83
Selecting the Stereo Pair................................................................................................................................................................................... 83
Navigating Within the 3-D Viewing Window ...................................................................................................................................................... 84
Moving the Stereo Cursor Pixel by Pixel ................................................................................................................................................... 85
Moving the Stereo Cursor to Different Elevations...................................................................................................................................... 85
Adjusting the Alignment in the Stereo Viewer ................................................................................................................................................... 85
Creating a Layer ................................................................................................................................................................................................ 85
Changing the Projection When Creating a New Layer .............................................................................................................................. 86
Loading a Layer................................................................................................................................................................................................. 87
Changing the Priority of a Layer ........................................................................................................................................................................ 87
Changing the Visibility of a Layer ...................................................................................................................................................................... 87
Changing the Color of the Vectors in a Layer.................................................................................................................................................... 87
Changing the Type of the Layer ........................................................................................................................................................................ 88
Adding Points to a Layer ................................................................................................................................................................................... 88
Adding Lines to a Layer..................................................................................................................................................................................... 88
Adding Polygons to a Layer............................................................................................................................................................................... 89
Using Snap to Vertex......................................................................................................................................................................................... 90
Using Snap to Line ............................................................................................................................................................................................ 90
Using the Vector Editing Tools .......................................................................................................................................................................... 90
Inserting a Vertex ...................................................................................................................................................................................... 91
Deleting a Vertex ....................................................................................................................................................................................... 91
Deleting a Line or Polygon ........................................................................................................................................................................ 92
Moving a Vertex or a Point ........................................................................................................................................................................ 92
Reversing an Action (Undo)....................................................................................................................................................................... 92
Designing the Attribute Table ............................................................................................................................................................................ 92
Assigning Attribute Values................................................................................................................................................................................. 93
Saving a Layer................................................................................................................................................................................................... 93
Deleting a Layer ................................................................................................................................................................................................ 94
Using Shortcuts in the 3-D Viewer..................................................................................................................................................................... 94
Extracting Vector Points from a Digital Elevation Model ................................................................................................................................... 95
Extracting Contour Lines from a Digital Elevation Model .................................................................................................................................. 96
v
Chapter 8
CORRECTING YOUR IMAGES
Understanding Orthorectification........................................................................................................................................................................ 97
Orthorectifying Your Images .............................................................................................................................................................................. 98
Understanding Elevation Scale and Offset ...................................................................................................................................................... 100
Understanding Geometric Correction............................................................................................................................................................... 100
Geometrically Correcting Your Images ............................................................................................................................................................ 101
Understanding Sampling Interval ..................................................................................................................................................................... 102
Understanding the Status Descriptions............................................................................................................................................................ 103
Troubleshooting Your Orthorectified Images ................................................................................................................................................... 104
Understanding the Resampling Options .......................................................................................................................................................... 104
Nearest (Nearest Neighbor Interpolation) ................................................................................................................................................ 105
Bilinear (Bilinear Interpolation) ................................................................................................................................................................. 105
Cubic (Cubic Convolution) ....................................................................................................................................................................... 105
Sin (8 Pt and 16 Pt SinX/X)...................................................................................................................................................................... 105
Average Filter........................................................................................................................................................................................... 106
Median Filter ............................................................................................................................................................................................ 106
Gaussian Filter ......................................................................................................................................................................................... 106
User Defined Filter ................................................................................................................................................................................... 106
Radar Gamma Filter................................................................................................................................................................................. 107
Radar Enhanced Frost Filter .................................................................................................................................................................... 108
Radar Kuan Filter ..................................................................................................................................................................................... 109
Radar Enhanced Lee Filter ...................................................................................................................................................................... 110
Chapter 9
MOSAICKING YOUR IMAGES
Understanding Mosaicking............................................................................................................................................................................... 111
Defining a Mosaic Area .................................................................................................................................................................................... 112
Editing the Mosaic Extents....................................................................................................................................................................... 113
Mosaicking Images with a Background Value Other Than Zero .............................................................................................................. 113
Mosaicking Images Automatically .................................................................................................................................................................... 113
Mosaicking Images Manually ........................................................................................................................................................................... 115
Adding an Image to the Mosaic................................................................................................................................................................ 115
Collecting the Cutline ............................................................................................................................................................................... 115
vi
Adjusting the Color Balance .................................................................................................................................................................... 116
Adding the Image to the Mosaic Area ..................................................................................................................................................... 116
Blending the Seams ................................................................................................................................................................................ 117
Understanding Cutlines ................................................................................................................................................................................... 117
Understanding Color Balancing....................................................................................................................................................................... 117
Changing the Layout in the Manual Mosaicking Window ................................................................................................................................ 118
Regenerating the Mosaic................................................................................................................................................................................. 118
Mosaicking Digital Elevation Models ............................................................................................................................................................... 119
Chapter 10
ADDITIONAL FEATURES
Understanding the Enhancements .................................................................................................................................................................. 121
Using Zoom, ReLoad and Pan ........................................................................................................................................................................ 122
Loading Vectors Over an Image ..................................................................................................................................................................... 122
Changing the Color of a Vector Layer ..................................................................................................................................................... 123
Cursor Control ................................................................................................................................................................................................. 123
Changing Image Color Channels .................................................................................................................................................................... 123
Selecting Image Channels............................................................................................................................................................................... 123
Removing Images............................................................................................................................................................................................ 124
Re-connecting Offline Images ......................................................................................................................................................................... 124
Renaming Images ................................................................................................................................................................................... 124
Synchronizing the Images ....................................................................................................................................................................... 125
Replacing Image Pixel Values......................................................................................................................................................................... 125
Converting the DEM Datum............................................................................................................................................................................. 126
Rejoining (Stitching) Image Tiles..................................................................................................................................................................... 126
Setting the Automatic Backup ......................................................................................................................................................................... 127
Setting Default Ground Control Point Elevation Units ..................................................................................................................................... 127
Setting a Default Ground Control Point Elevation Datum................................................................................................................................ 128
Changing the Default Orthorectification or Mosaic Output Format .................................................................................................................. 128
Setting the Channel Type for Your Output Image ........................................................................................................................................... 129
Understanding When To Build Overviews....................................................................................................................................................... 129
Exporting the Math Model................................................................................................................................................................................ 129
Exporting the Ground Control Points............................................................................................................................................................... 130
Exporting the Exterior Orientation ................................................................................................................................................................... 131
Exporting to Supresoft Format......................................................................................................................................................................... 131
vii
Changing the Default Color Ground Control Points and Tie Points ................................................................................................................. 131
Setting the Threshold Values for the Math Models (Bundle Options) .............................................................................................................. 131
Generating a Project Report ............................................................................................................................................................................ 132
Saving the Project as a Template .................................................................................................................................................................... 133
Using the File Utility ......................................................................................................................................................................................... 133
Viewing an Image Outside Your Project .......................................................................................................................................................... 133
Understanding Format Descriptions for Text Files Containing GCPs .............................................................................................................. 133
Chapter 11
CREATING A CHIP DATABASE
Understanding the Chip Manager .................................................................................................................................................................... 135
Opening the PCI Chip Manager ....................................................................................................................................................................... 135
Creating a New Database ................................................................................................................................................................................ 135
Opening an Existing Chip Database ................................................................................................................................................................ 136
Selecting the Source for the Chips................................................................................................................................................................... 136
Working in the Chip Manager Viewers............................................................................................................................................................. 137
Collecting the Chip ........................................................................................................................................................................................... 137
Determining the Size of the Chip ..................................................................................................................................................................... 137
Creating Chips from a GCP Segment .............................................................................................................................................................. 138
Changing the Location of the GCP .................................................................................................................................................................. 138
Searching the Chip Database .......................................................................................................................................................................... 139
Creating a New Chip Database from an Existing Database ............................................................................................................................ 139
Merging Chip Databases.................................................................................................................................................................................. 139
Deleting a Chip Database ................................................................................................................................................................................ 139
Deleting a Chip from the Database .................................................................................................................................................................. 140
Defragmenting a Chip Database...................................................................................................................................................................... 140
Generating Reports.......................................................................................................................................................................................... 140
Setting the Source Image Default Parameters................................................................................................................................................. 140
Changing the Colors of the Cursors................................................................................................................................................................. 141
Index ............................................................................................................................................................................................................... 143
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CHAPTER
1
Using OrthoEngine
Introducing Geomatica OrthoEngine
Welcome to Geomatica OrthoEngine. OrthoEngine is a powerful
photogrammetric tool designed to handle small and large production
workloads to efficiently produce quality geospatial products.
Geomatica’s Generic Database (GDB) technology provides you with
seamless and direct geospatial data transfer capabilities, which means
that you can import, export, or read directly over 100 raster and vector
formats. OrthoEngine supports images from standard aerial, digital,
and video cameras, and data from satellite sensors such as:
• ASAR
• ERS
• JERS
• QUICKBIRD
• ASTER
• IKONOS
• LANDSAT
• RADARSAT
• AVHRR
• IRS
• MERIS
• SPOT
• EOC
OrthoEngine’s interface is organized along logical workflows to
produce orthorectified or geometrically corrected images, digital
elevation models (DEMs), three-dimensional vectors, and mosaics.
This structure provides you with a more intuitive workflow.
To help you complete your projects more efficiently, OrthoEngine
includes several features that can save you time and effort, and will
provide you with more accurate results. For example:
• Rigorous math models produce robust orthorectification of aerial and
satellite imagery such as QuickBird data.
• The enhanced viewer offers increased zoom capabilities, panning,
brightness, contrast, cursor control, and mapping color channels.
• Automatic fiducial mark collection saves time when you import photos.
• Automatic tie point collection quickens the tedious process of
collecting tie points.
• Epipolar batch processing converts a group of stereo pairs into
epipolar image pairs, which shortens the process for Automatic
DEM Extraction and 3-D Feature Extraction.
• Automatic DEM Extraction can start batch processing for the epipolar
pairs, and generate and automatically geocode a single, seamless DEM
in one process.
• Selecting multiple images to orthorectify or geometrically correct
streamlines the process.
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Chapter 1 - Using OrthoEngine
• Improved color balancing in Automatic Mosaicking reduces the need to
refine the results.
Getting Started
The work flow that you choose depends on what you want to achieve.
If you have a clear idea of what you want to obtain from your project,
it will be easier to work through your project and achieve the results
that you want.
• Generate Digital Elevation Models (DEMs). A digital
elevation model is a digital file of terrain elevations. For more
information, see “Understanding Digital Elevation Models” on
page 63.
• Edit features in three-dimensions (3-D). You can view and
extract features in 3-D from a pair of stereo images using
anaglyph or shutter displays. For more information, see
“Understanding 3-D Stereo Viewing and Editing” on page 81.
3. Decide which images you want to use.
When you start a project:
1. Determine the accuracy and resolution requirements for your project.
Knowing the level of accuracy that you want to obtain, the resolution
of your deliverable (final output), the file size limitations, and the
extent of your budget will help you to make the right decisions about
how you build your project.
Depending on what you decided in step 1, do you need aerial
photographs or satellite images? If you are going to use aerial
photographs, you need to decide at what altitude the aircraft should
fly, what camera type will be used, and plan the flight lines. If you are
going to use satellite imagery, you must decide from which sensor
you want to acquire your imagery.
4. Collect control information.
2. Determine your deliverable.
What do you want as the end result of your project? OrthoEngine can:
• Orthorectify images. Orthorectified images (Orthos) are
geometrically corrected and georeferenced imagery.
Orthorectification is the process of using a rigorous math model
and a digital elevation model (DEM) to correct distortions in raw
images. For more information, see “Understanding
Orthorectification” on page 97.
• Geometrically correct images. Geometric Correction is the
process of using ground control points (GCPs) to calculate a
simple math model that will warp the raw image to fit the ground
coordinates. For more information, see “Understanding
Geometric Correction” on page 100.
• Mosaic. Mosaicking is the process of joining corrected images
into a seamless image map. For more information, see
“Understanding Mosaicking” on page 111.
2
You can obtain ground control points from sources such as GPS data,
surveys, scanned maps, and vector databases. You can use existing
DEMs that cover your area of interest to aid in identifying elevations.
For more information, see “Collecting Control Points and Computing
the Math Models” on page 33.
Working with OrthoEngine
As you follow instructions in the printed manual and the online help
system, you will find a special note that looks like this:
Next step in your project . . .
This note guides you through your project by indicating the next step
according to the decisions that you make.
PCI Geomatics
Working with OrthoEngine
After you have gathered the information that you need to start your
project (as explained in “Getting Started” on page 2), you can open
OrthoEngine (see “Starting OrthoEngine” on page 9) and begin.
Figure 1.1: Simplified Work flows
Step 1: Set up the project
• Select the math model
• Set the projection
• Import images
• Enter data about the sensor geometry (for rigorous models only)
Step 2: Compute the math model
• Collect the ground control points (GCPs)
• Collect the tie points
• Compute the solution of the math model
• Verify the math model solution
Step 3: Generate the deliverable(s)
• Generate a digital elevation model (DEM)
• Generate three-dimensional vectors (3-D Feature Extraction)
• Orthorectify or geometrically correct the images
• Mosaic images
Combining the deliverables:
As you can see in Figure 1.1, two of the deliverables are not only
products in themselves, but can also be used to form other products.
For example, you can take your orthorectified or corrected images and
join them to form a mosaic. If you do not have an existing DEM for
your project area, you can generate a DEM from image stereo pairs in
your project and use it to orthorectify your images.
OrthoEngine User’s Guide
3
Chapter 1 - Using OrthoEngine
How To Contact Us
Software support is available from PCI Geomatics to assist you with
technical or application difficulties. Please call your PCI Geomatics
representative or authorized reseller to obtain more information about
software support.
Suggestions for future versions of PCI Geomatics products:
[email protected]
On the Web:
http://www/support/support.html
Before you contact us, please have the following information ready:
By fax:
• Your customer number
Fax: +1 (905) 764-9604 (attention: support)
• Product name
• Product version
• Computer system and O/S version
• Exact error message, if any
• Steps to re-create the problem
• Your phone number, fax number, and e-mail address
By mail:
PCI Geomatics
50 West Wilmot Street
Richmond Hill, Ontario
Canada L4B 1M5
Attention: Technical Support
By telephone:
1-877-RING-PCI (1-877-746-4724) (North America)
+800 2746 4724 (toll free from the United Kingdom, The Netherlands,
Belgium, and France)
+44 1491 579 910 (Direct to our European support office)
1-905-764-0614 (Direct to our main office)
By e-mail:
[email protected]
[email protected]
Training course information: [email protected]
4
PCI Geomatics
CHAPTER
2
Starting your Project and Selecting a Math Model
Understanding the Math Models
A math model is a mathematical relationship used to correlate the
pixels of an image to correct locations on the ground accounting for
known distortions. The math model that you choose directly impacts
the outcome of your project. To achieve the results that you are looking
for, you need to understand what the math models do, what the math
models require to produce an acceptable solution, and which math
model to use with your project. You can use one of five math models:
as the curvature of the lens, the focal length, the perspective effects,
and the camera’s position and orientation. The computed math model
calculates the camera’s position and orientation at the time when the
image was taken.
You should not use the Aerial Photography Math Model when you are
using only a portion of the original image, when the image has been
geometrically processed, or when you do not have (or cannot estimate)
the camera calibration information.
• Aerial Photography
• Satellite Orbital
Understanding Satellite Orbital Modelling
• Rational Functions
The Satellite Orbital Math Model is a rigorous model developed by Dr.
Toutin at the Canada Center for Remote Sensing to compensate for
distortions; such as sensor geometry, satellite orbit and attitude
variations, and earth shape, rotation, and relief. This model can be
applied to ASTER, AVHRR, IKONOS, LANDSAT, SPOT, IRS,
QuickBird, and radar images; such as ASAR (beta support),
RADARSAT, ERS-1 and JERS1. The computed math model calculates
the position and orientation of the sensor at the time when the image
was taken.
• Polynomial
• Thin Plate Spline
Understanding the Aerial Photography Math Model
The Aerial Photography Math Model is a rigorous model based on the
geometry of a frame camera. This model can compensate for the effects
of varying terrain and for the distortions inherent to the camera; such
5
Chapter 2 - Starting your Project and Selecting a Math Model
For IKONOS images, also see “Using the Right Math Model with
IKONOS Data” on page 6.
You should not use the Satellite Orbital Math Model when you are
using only a portion of the original image, when the image has been
geometrically processed, or when you do not have (or cannot estimate)
the orbit information.
The Satellite Orbital Math Model is based on the co-linearity
condition, which represents the physical law of transformation
between the image space and the ground space. It uses principles
related to photogrammetry, orbitography, geodesy, and cartography.
The model reflects the physical reality of the complete viewing
geometry, and reflects all the distortions generated during the image
formation; such as those caused by:
• The platform (position, velocity, and orientation)
Using the Right Math Model with IKONOS Data
Space Imaging distributes IKONOS data in a variety of products, but
does not release the orbit data. Their most economical product,
IKONOS GEO, is a simple image file with positional accuracy of up to
150 meters, not including terrain effects. To orthorectify IKONOS
GEO images, use the Satellite Orbital math model, which provides 3to 4-meter accuracy with the collection of 20 or more ground control
points (GCPs).
Space Imaging’s IKONOS GEO Ortho Kit product is a Geotiff
combined with a text file that contains rational function coefficients,
called Image Geometry Model (IGM) or Rapid Positioning Capability
(RPC). The Ortho Kit product also contains no orbit data, but the text
file provides the coefficients to define the Rational Functions math
model. Using the Rational Functions math model with the Geotiff and
the text file provides 10- to 25-meter accuracy. However, adding one
or two GCPs improves the accuracy to 3- to 4-meters.
• The sensor (orientation, integration time, and field of view)
• The earth (geoid, ellipsoid, and relief)
• The cartographic projection (ellipsoid and cartographic)
As a result of this integration, the modelling equations are simple and
straightforward with few unknowns. Each of the unknowns is the
combination of several correlated variables of the viewing geometry,
so the number of unknowns is reduced to an independent set. The
equations are then solved with few ground control coordinates, and
with tie points if more than one image is used. You can create a project
using images acquired from one satellite or from a combination of
images from different satellites.
The accuracy of the Satellite Orbital Math Model is approximately
one-third of a pixel for VIR satellite images, and approximately one
pixel for radar images when quality ground control coordinates are
used. Dr. Toutin proved the accuracy of this math model by testing it
using many different images of different areas and relief.
You can also use the Satellite Orbital math model with the Geotiff from
the Ortho Kit (the text file is ignored).
Understanding the Rational Functions Math Model
The Rational Functions Math Model is a simple math model that builds
a correlation between the pixels and their ground locations. Use this
math model when you are missing the information needed for a
rigorous math model, when the sensor model is proprietary (classified),
when the image has been geometrically processed, when the data
provider computed the math model and distributed it with the image,
or when you do not have the whole image.
The Rational Functions Math Model can be more accurate than the
Polynomial or Thin Plate Spline Math Models since it considers
elevations. However, it can require many ground control points
(GCPs).
The math model is computed for each image separately. The Rational
Functions Math Model uses a ratio of two polynomial functions to
6
PCI Geomatics
Understanding the Math Models
compute the image row, and a similar ratio to compute the image
column. All four polynomials are functions of three ground
coordinates: latitude, longitude, and height or elevation. The
polynomials are described by using a set of up to 20 coefficients,
although some of the coefficients are often zero.
The polynomial coefficients, often called Rapid Positioning Capability
(RPC) data, can be obtained in two ways:
• You collect a number of GCPs, and OrthoEngine calculates the
polynomial coefficients automatically. The minimum number of
required GCPs is determined by multiplying the number of coefficients
by 2 and then subtracting 1. For example, if you wanted to use 10
coefficients, you would multiply 10 by 2 and then subtract 1, which
means you would need 19 GCPs per image. You set the number of
coefficients that you want to use on the GCP Collection windows
under Auxiliary Information, see “Collecting Control Points and
Computing the Math Models” on page 33.
• The image distribution agency computes the polynomial coefficients
for each image and distributes the data with the images. This is only
available for IKONOS imagery, QuickBird imagery, or images that are
distributed in NITF 2.0 format with the RPC image support data
included in the NITF file. Space Imaging distributes the IKONOS
Ortho Kit imagery with an auxiliary text file, called an Image Geometry
Model (IGM), containing the coefficients. The coefficients are
automatically imported into OrthoEngine. However, adding GCPs can
refine the math model of a project using IKONOS imagery (see “Using
the Right Math Model with IKONOS Data” on page 6).
Note
Using more coefficients will result in a more accurate fit in the immediate
vicinity of the GCPs, but it may introduce new and significant errors in the
image away from the GCPs. The errors introduced into the imagery may be
worse than the original errors that needed correcting. We recommend using
10 coefficients since it usually produces the best results.
The three ground coordinates and two image coordinates are each
offset and scaled to have a range from -1.0 to +1.0 over the image. For
each image the defined ratios of polynomials have the form:
P1 ( Xn, Yn, Zn )
Row n = -----------------------Q2 ( Xn, Yn, Zn )
P2 ( Xn, Yn, Zn )
Col n = -----------------------Q2 ( Xn, Yn, Zn )
where:
Row n = Normalized row index of pixel in image
Col n = Normalized column index of pixel in image
Xn, Yn, Zn = Normalized ground coordinate values
The polynomials P and Q have the form:
m1
P =
m2
m3
∑ ∑ ∑
i j k
Aijk Xn Yn Zn
∑ ∑ ∑
i j k
Bijk Xn Yn Zn
i=0j=0 k=0
n3
n1
n2
Q =
i=0j=0 k=0
where:
Aijk and Bijk = Polynomial coefficients
The maximum power for each ground coordinate (m1, m2, m3, n1, n2,
and n3) is limited to 3, and the total power of all three ground
coordinates is limited to 3. That is, the polynomial coefficients are
defined to be zero whenever i+j+k > 3.
Understanding the Polynomial Math Model
The Polynomial Math Model is a simple math model that uses a firstthrough-fifth order polynomial transformation, which is calculated
OrthoEngine User’s Guide
7
Chapter 2 - Starting your Project and Selecting a Math Model
based on two-dimensional (2-D) ground control points (GCPs). This
math model produces the “best” fit mathematically to a set of 2-D
GCPs on an image.
The polynomial equations are fitted to the x and y coordinates of the
GCPs by using least squares criteria to model the correction in the
image without identifying the source of the distortion. You can choose
one of several polynomial orders depending on the desired accuracy
and the number of GCPs available.
First-order polynomial transformations can model a rotation, a scale
and a translation. As up to 21 additional terms are added, giving a fifthorder polynomial, you can achieve more complex warping. However,
using a lower order transformation reduces the time needed to
complete the correction, and less geometric distortion may occur in
areas with no GCPs.
The result of a first-order transformation depends on the number of
GCPs:
• One GCP produces a translation for x and y only.
• Two GCPs produce a translation and a scaling change for x and y, if the
pixel geometry is not linear in the x or y dimension. If it is linear,
meaning that the two GCPs have the same x or y coordinate producing
a scaling factor of zero, it produces only a translation. If the scaling
factor is greater than zero, it may produce a flip in the x and/or y
dimension.
• Three or more GCPs produce a translation, scale change and/or rotation
for x and y: a full first-order transformation.
Note
Understanding the Thin Plate Spline Math Model
The Thin Plate Spline Math Model is a simple math model in which all
the collected ground control points (GCPs) are used simultaneously to
compute a transformation. The warping is distributed throughout the
image with minimum curvature between the GCPs becoming almost
linear away from the GCPs.
The Thin Plate Spline Math Model fits the GCPs exactly. Therefore, a
GCP can be added in an area where the transformation is not
satisfactory. However, this also means that the math model does not
provide direct means of detecting and correcting errors in GCP
coordinates. To verify the derived transformation, you should acquire
a number of Check Points large enough to ensure a thorough
verification such as an amount equal to half the number of GCPs. For
more information about Check Points, see “Troubleshooting the Math
Model Solution” on page 56.
The Thin Plate Spline Math Model can handle more variation in terrain
than the Polynomial Math Model, because it recognizes threedimensional GCPs and minimizes the extrapolation errors that can
occur between the GCPs.
To compute a warping transformation accurately, you should collect
GCPs at the extremes of the terrain and along the breaklines. If you use
the Thin Plate Spline Math Model with an image in rough terrain, it
may be necessary to acquire hundreds of GCPs. For this reason, the
Thin Plate Spline Math Model is recommended only for distortions that
can be accurately represented using up to a few dozen GCPs. It is not
recommended for the removal of terrain distortions or for images of
rough terrain. A rigorous model, such as the Satellite Orbital or Aerial
Photography Math Model, may be the better choice in these cases.
A higher order polynomial will result in a more accurate fit in the immediate
vicinity of the GCPs, but it may introduce new and significant errors in the
image away from the GCPs. The errors introduced into the imagery may be
worse than the original errors that needed correcting.
8
PCI Geomatics
Starting OrthoEngine
Starting OrthoEngine
or when you do not have (or cannot estimate) the camera calibration
information.
To start OrthoEngine, choose one of the following:
1. From Windows®, click the Start button, click Programs, click PCI
Geomatics, and then click OrthoEngine.
To start the project:
2. If Geomatica is running, click
Geomatica Toolbar.
2. On the Project Information window in the Filename box, type a file
name for your project. This will be the name used when you save your
project.
the OrthoEngine icon on the
3. For Unix® after you have set up the path for Geomatica , type in the
prompt: orthoeng.exe.
Next step in your project . . .
Depending on the math model that you are using, select one:
“Starting a Project Using the Aerial Photography Math Model” on page 9.
“Starting a Project Using the Satellite Orbital Math Model” on page 10.
“Starting a Project Using the Rational Functions Math Model” on page 11.
“Starting a Project Using the Polynomial Math Model” on page 11.
“Starting a Project Using the Thin Plate Spline Math Model” on page 12.
“Starting a Project to Mosaic Existing Georeferenced Images” on page 12.
Starting a Project Using the Aerial
Photography Math Model
The Aerial Photography Math Model is a rigorous model that
compensates for known distortions to calculate the position and
orientation of the camera at the time when the image was taken. For
more information, see “Understanding the Aerial Photography Math
Model” on page 5.
You should not use the Aerial Photography Math Model when you are using
only a portion of the original image, when the image has been processed,
OrthoEngine User’s Guide
1. On the OrthoEngine window in the File menu, click New.
3. In the Name box, type a name that you want to appear on the title bar of
the OrthoEngine window.
4. In the Description box, type a description of the project that will help
you to identify its contents.
5. Under Math Modelling Method, click Aerial Photography.
6. In the Camera Type list, select the camera type corresponding to the
images that you are using in your project:
• Click Standard Aerial Camera when the images are scanned
from film or paper prints. These often measure 9 inches by 9
inches in size and usually contain calibration (fiducial) marks.
Normally, a camera calibration report is supplied with the images.
The camera calibration report provides data about the camera;
such as the focal length, fiducial coordinates, and radial distortion
parameters. For more information, see “Understanding Camera
Calibration Data” on page 21.
• Click Digital/Video Camera when the frame images are
generated from CCD arrays (Charged Coupled Devices). A
camera calibration report is often not supplied with the images.
However, most companies that provide calibration services for
standard aerial cameras can provide camera calibration services
for digital and video cameras (for more information, see
“Understanding Camera Calibration Data” on page 21). The
minimum measurements required are the focal length, which is
9
Chapter 2 - Starting your Project and Selecting a Math Model
determined when the lens is set, and the chip size, which can be
obtained from the camera manufacturer.
7. In the Exterior Orientation list, select the source of the exterior
orientation for your project:
• Click Compute from GCPs and tie points when you intend to
use known points and/or coordinates on the ground to establish
the camera’s position when the image was taken.
• Click User Input when you intend to import the exterior
orientation that was calculated in a previous project or by another
triangulation software (see “Setting Up Camera Calibration and
Aerial Photographs” on page 21).
8. Click Accept.
Tip
Many aircraft are equipped with onboard Global Positioning Systems
(GPS), and sometimes with Inertial Navigation Systems (INS) as well.
These systems collect the exterior orientation of the camera directly on the
aircraft.
Select User Input to use the GPS and INS readings (navigation solution)
alone and accept them as correct. Select Compute from GCPs and tie
points to use ground control points and/or tie points to refine the GPS and
INS results.
Next step in your project . . .
See “Setting the Projection” on page 13.
To start the project:
1. On the OrthoEngine window in the File menu, click New.
2. On the Project Information window in the Filename box, type a file
name for your project. This will be the name used when you save your
project.
3. In the Name box, type a name that you want to appear on the title bar
of the OrthoEngine window.
4. In the Description box, type a description of the project that will help
you to identify its contents.
5. Under Math Modelling Method, click Satellite Orbital Modelling.
For IKONOS images, see “Using the Right Math Model with
IKONOS Data” on page 6.
6. Under Options, select the sensor type corresponding to the images that
you are using in your project:
• Click Toutin’s Model when you are using high resolution optical
or radar satellite sensors; such as LANDSAT, RADARSAT,
SPOT, or IKONOS.
• Click ASAR/RADARSAT Specific Model when you want to use
the additional parameters in RADARSAT’s orbit data to diminish
amount of ground control points (GCPs) required. The extra
parameters maintain the positional accuracy and high levels of
detail in the model, but the number of GCPs needed is reduced to
few or none. This math model does not use tie points since each
scene is computed using the GCPs of that scene only.
• Click Low Resolution when you use low resolution sensors such
as AVHRR.
Starting a Project Using the Satellite
Orbital Math Model
7. Click Accept.
The Satellite Orbital Math Model is a rigorous model that compensates
for known distortions to calculate the position and orientation of the
sensor at the time when the image was taken. For more information, see
“Understanding Satellite Orbital Modelling” on page 5.
Next step in your project . . .
See “Setting the Projection” on page 13.
10
PCI Geomatics
Starting a Project Using the Rational Functions Math Model
Starting a Project Using the Rational
Functions Math Model
The Rational Functions Math Model is a simple math model that builds
a correlation between the pixels and the ground locations. For more
information, see “Understanding the Rational Functions Math Model”
on page 6.
To start the project:
Tip
When you are using the IKONOS GEO Ortho Kit, you can achieve up to 3to 4-meter accuracy by adding one or two quality GCPs for each image.
Next step in your project . . .
See “Setting the Projection” on page 13.
1. On the OrthoEngine window in the File menu, click New.
2. On the Project Information window in the Filename box, type a file
name for your project.
Starting a Project Using the Polynomial
Math Model
3. In the Name box, type a name that you want to appear on the title bar of
the OrthoEngine window.
The Polynomial Math Model is a simple math model that produces the
best mathematical fit to a set of two-dimensional ground control points
(GCPs). For more information, see “Understanding the Polynomial
Math Model” on page 7.
4. In the Description box, type a description of the project that will help
you to identify its contents.
5. Under Math Modelling Method, click Rational Functions.
To start the project:
6. Under Options, select the source of the coefficients for the Rational
Function Math Model:
1. On the OrthoEngine window in the File menu, click New.
• Click Compute from GCPs when the Rational Functions
coefficients are calculated based on the ground control points
(GCPs) that you collect.
• Click Extract from Image File when you want to import the
coefficients from a file. Some data providers compute the
Rational Functions coefficients based on their knowledge of the
sensor and distribute the coefficients and the image in an NITF
file. Also, the IKONOS GEO Ortho Kit and QuickBird Basic with
RPC Kit products contain a text file with the coefficients.
2. On the Project Information window in the Filename box, type a file
name for your project.
3. In the Name box, type a name that you want to appear on the title bar of
the OrthoEngine window.
4. In the Description box, type a description of the project that will help
you to identify its contents.
5. Under Math Modelling Method, click Polynomial.
6. Click Accept.
7. Click Accept.
OrthoEngine User’s Guide
11
Chapter 2 - Starting your Project and Selecting a Math Model
Next step in your project . . .
See “Setting the Projection” on page 13.
Starting a Project to Mosaic Existing
Georeferenced Images
To start the project:
Starting a Project Using the Thin Plate
Spline Math Model
The Thin Plate Spline Math Model is a simple math model in which all
the collected ground control points (GCPs) are used simultaneously to
perform a transformation. For more information, see “Understanding
the Thin Plate Spline Math Model” on page 8.
To start the project:
1. On the OrthoEngine window in the File menu, click New.
2. On the Project Information window in the Filename box, type a file
name for your project. This will be the name used when you save your
project.
3. In the Name box, type a name that you want to appear on the title bar
of the OrthoEngine window.
4. In the Description box, type a description of the project that will help
you to identify its contents.
5. Under Math Modelling Method, click Thin Plate Spline.
6. Click Accept.
Next step in your project . . .
See “Setting the Projection” on page 13.
1. On the OrthoEngine window in the File menu, click New.
2. On the Project Information window in the Filename box, type a file
name for your project. This will be the name used when you save your
project.
3. In the Name box, type a name that you want to appear on the title bar
of the OrthoEngine window.
4. In the Description box, type a description of the project that will help
you to identify its contents.
5. Under Math Modelling Method, click None (Mosaic Only).
6. Click Accept.
Next step in your project . . .
See “Setting the Projection”.
Understanding Projections and Datums
A projection represents the earth's irregular three-dimensional surface
as a flat surface. A map projection is used to transform the locations of
features on the earth's surface to locations on a two-dimensional plane.
A variety of map projections exist, usually based on one of the three
basic types: azimuthal, conical, and cylindrical. For example, the
Transverse Mercator Projection is a variation of the cylindrical
projection.
A datum is a mathematical surface used to make geographic
computations. An ellipsoid approximates the size and shape of all or
part of the earth. The datum includes parameters to define the size and
12
PCI Geomatics
Setting the Projection
shape of the ellipsoid used, and its position relative to the center of the
earth. Geographic coordinate systems use different datums to calculate
positions on the earth.
If you compare the same point using two different datums or
projections, the coordinates of the point will be different. Referencing
a project’s coordinates to the wrong datum or using the wrong
projection may result in features being offset by significant distances.
Different projections and datums introduce different distortions or
warping into the image. You should choose the projection and datum
that will give you the results that you expect for your project. If you are
using data from multiple projections, OrthoEngine can only re-project
the coordinates correctly if the projection and datum are set properly.
For Reference
For more information, read:
Iliffe, J.C. Datums and Map Projections for Remote Sensing, GIS and
Surveying, Whittles Publishing: Caithness, Scotland, 2000.
Kennedy, Melita. Understanding Map Projections, Environmental Systems
Research Institute, Inc.: Redlands, CA, 1999.
Maling, D.H. Coordinate Systems and Map Projections, Pergamon Press
Ltd.: Oxford England, 1992.
Map Projections: Georeferencing Spatial Data, Environmental Systems
Research Institute, Inc.: Redlands, CA, 1994.
Snyder, J.P. and Philip M. Voxland. An Album of Map Projections. U.S.
Geological Survey Professional Paper 1453, USGS: Washington
D.C.,1989.
Setting the Projection
A projection is a method of portraying all or part of the earth on a flat
surface. For more information, see “Understanding Projections and
Datums” on page 12.
The Output Projection defines the final projection for orthoimages,
mosaics, 3-D features, and digital elevation models (DEMs).
OrthoEngine User’s Guide
The GCP Projection is the default used during manual ground control
point (GCP) collection to specify the projection of the collected GCPs
or when importing GCPs from text file. If you collect GCPs from a
geocoded source, the coordinates are re-projected to the GCP
Projection and saved into the project file.
If you collect GCPs from multiple sources, you can change the GCP
Projection to match each source using the Set Projection window.
Using different projections increases processing time during
orthorectification. It is always more efficient to work with one
projection.
Tip
If you are working on a Mosaic Only project, you can click Cancel on the
Set Projection window. The output projection and resolution will be set
automatically from the first image that you add to your project.
The Set Projection window may open automatically after completing
the Project Information window. If it is open, skip to step 3.
To set the projection:
1. On the OrthoEngine window in the Processing Step list, select
Project.
2. Click
the Set Output and Default Projection icon.
3. On the Set Projection window under Output Projection, type the
projection string (for example, UTM 17 T D000) in the text box
beside the Earth Model button.
If you do not know the projection string:
• Select a projection type from the list to the left of the Earth
Model button.
(For UTM, State Plane Coordinate Systems (SPCS), or Other
projection types, additional windows may open automatically for
you to select the parameters to define the projection or click
13
Chapter 2 - Starting your Project and Selecting a Math Model
More to open these windows. Select the parameters and click
Accept.)
• Click Earth Model.
• Click either the Datum or Ellipsoid tab.
• Click a datum or an ellipsoid.
• Click Accept.
If the output projection is State Plane Coordinate in feet or FOOT
projection (SPAF, SPIF, and FOOT), all calculations are in feet.
DEMs can be in either feet or meters as long as the GCP Elevation
Units are set for GCP collection, and the elevation units are set on the
Ortho Image Production window. If the output projection is changed
and there are some existing GCPs that cannot be projected onto the
new output projection, they are changed into Check Points so that
they do not affect the computation of the math model.
4. In the Output Pixel Spacing box, type the x pixel size in the units
(meters, feet, or degrees) used in the project.
5. In the Output Line Spacing box, type the y pixel size in the units
(meters, feet, or degrees) used in the project.
If you change the values for the Output Pixel Spacing or Output Line
Spacing, all orthoimages created previously are reset automatically to
None and should be regenerated at the new resolution. Also, the output
mosaic is reset when the resolution changes. The previous files are not
removed from the disk, but the status in the project file is reset to None.
Next step in your project . . .
For Aerial Photography Projects, see “Entering the Camera Calibration
Data” on page 24.
For Satellite Orbital Projects, see “Importing and Viewing Images” on
page 15.
For Rational Functions, Polynomial, and Thin Plate Spline Projects, see
“Collecting Control Points and Computing the Math Models” on page 33.
For Mosaic Only, see “Importing Images or Photographs into Your Project”
on page 15.
For orthoimages and mosaics, the Output Pixel Spacing and Output
Line Spacing are the x and y resolution of your output images.
6. Under GCP Projection, select a projection type.
7. Under GCP Projection, type the projection string (for example, UTM
17 T D000) in the text box beside the Earth Model button or click
Set GCP Projection based on Output Projection if your GCP
projections are the same as your output projection.
If you do not know the projection string, follow the same steps
described under step 3.
8. On the Set Projection window, click Accept.
14
PCI Geomatics
CHAPTER
3
Importing and Viewing Images
Importing Images or Photographs into
Your Project
You can import satellite images without ephemeris data, scanned
images from aerial photographs, digital images, and video images by
using the following method. To import satellite images with ephemeris
data, see “Reading Satellite Images from a CD or a Digital Distribution
Format” on page 15.
To import images into your project:
1. On the OrthoEngine window in the Processing Step list, select
Data Input or GCP Collection.
2. Click
the Open new or existing photo icon.
Next step in your project . . .
For photographs, see “Collecting Fiducial Marks Manually” on page 25.
For Mosaic Only projects, see “Defining a Mosaic Area” on page 112
For other projects, see “Understanding Ground Control Points” on page 33.
Reading Satellite Images from a CD or a
Digital Distribution Format
OrthoEngine reads the raw satellite data, saves the imagery into a
PCIDSK file, and adds a binary segment containing the ephemeris data
(orbit information) to the file. If your satellite images do not contain
ephemeris data, see “Importing Images or Photographs into Your
Project” on page 15.
3. Click New Photo.
4. In the Database File Selection window, select the images that you
want to import into your project. You can use SHIFT+left click or
CTRL+left click to select multiple files.
5. Click Open.
To read images from a CD or a digital distribution format:
1. On the OrthoEngine window in the Processing Step list, select
Data Input.
2. Click
the Read CD-ROM icon.
15
Chapter 3 - Importing and Viewing Images
3. Under Data Source in the CD Format box, select the sensor and
distribution format combination that corresponds to your data.
4. If the image channels are separated into several files, select or type
the name of the first file. Depending on the format,
• Click Select to select the file.
Reading Satellite Data from a Tape
OrthoEngine reads the raw satellite data, saves the imagery into a
PCIDSK file, and adds a binary segment containing the orbit
information to the file. Before reading image data from a magnetic
tape, the tape must be mounted. For information about mounting tape
drives, see the Installing PCI Software User Guide.
• In the CD Image Filename box select an image.
• In the CD Header Filename box select the header file.
To read satellite data from a tape:
If the CD Format is NLAPS LANDSAT, then you should specify the
name of the CD header filename instead of the CD image filename.
1. On the OrthoEngine window in the Processing Step list, select
Data Input.
5. Click the Requested Channels buttons corresponding to the channels
that you want import. Select at least one channel. For each PCIDSK file
that you create, all the selected channels must have matching spatial
resolution. For satellite images with multiple resolutions, import each
resolution into a separate PCIDSK file.
6. If the CD Format is CEOS RADAR, then you must select the SAR
Type. Select ERS or RADARSAT.
7. Under Data Output in the PCIDSK Filename box, type the name of
the output file.
8. In the Scene Description box, type a description of the file (optional).
9. In the Report Filename box, type the name of the file where the report
will be saved.
10. Click Read.
Next step in your project . . .
See “Collecting Control Points and Computing the Math Models” on
page 33.
2. Click
the Read Tape icon.
3. Under Data Source in the Tape Format box, select the sensor and
distribution format combination that corresponds to your data.
4. In the Tape Device box, type the path to the Tape drive. On Windows
systems, the Tape Device is the drive letter where the tape drive is
mounted. On Unix systems, Tape Device is the name of the directory
where the tape drive is mounted.
5. Click the Requested Channels buttons corresponding to the channels
that you want import. Select at least one channel. For each PCIDSK file
that you create, all the selected channels must have matching spatial
resolution. For satellite images with multiple resolutions, import each
resolution into a separate PCIDSK file.
6. If the Tape Format is CEOS RADAR, then you must select the SAR
Type. Select ERS or RADARSAT.
7. Under Data Output in the PCIDSK Filename box, type the name of
the output file.
8. In the Scene Description box, type a description of the file (optional).
9. In the Report Filename box, type the name of the file where the
report will be saved.
10. Click Read.
16
PCI Geomatics
Reading Satellite Data from a Generic Image File
Next step in your project . . .
See “Collecting Control Points and Computing the Math Models” on
page 33.
Next step in your project . . .
See “Collecting Control Points and Computing the Math Models” on
page 33.
Reading Satellite Data from a Generic
Image File
Importing Satellite Data from a PCIDSK
File
You can create an orbital model for image formats that do not have
embedded orbital ephemeris data by manually entering information
about the satellite image and orbit data.
If you have satellite imagery and orbit ephemeris data that is saved into
a PCIDSK file, you can add the data into your project.
To import satellite data from a PCIDSK file:
To read satellite data from a generic image file:
1. On the OrthoEngine window in the Processing Step list, select
Data Input.
2. Click
the Read Generic Image File icon.
3. In the Read Generic Image File window in the Input File box, type
the filename of the generic image file or click Browse to select the file.
The input file can be in any supported format.
4. In the Output File box, type the filename where you want to save the
project or click Browse to select a folder. The output file will be
saved in the PCIDSK format.
5. Under Satellite Information, enter information about the sensor.
6. Under Orbit and Sensor Information, enter the orbit information
and the values specific to the sensor (obtained from the sensor's
technical manual).
1. On the OrthoEngine window in the Processing Step list, select
Data Input.
2. Click
the Read PCIDSK File icon.
3. In the Database File Selection window, select the image that you
want to import into your project. Click Open.
Next step in your project . . .
See “Collecting Control Points and Computing the Math Models” on
page 33.
Opening Images
To view an image in your project:
1. On the OrthoEngine window in the Processing Step list, select
GCP Collection.
7. Under Image Information, enter the image's information, including
the image resolution, the latitude, the longitude, and the corresponding
ellipsoid of the scene center.
2. Click
8. Click Start Orbit Calculation.
3. In the Open Photo window, click an image.
OrthoEngine User’s Guide
the Open new or existing photo icon.
17
Chapter 3 - Importing and Viewing Images
4. Click:
• Open to open the image and select the bands to display.
• Quick Open to open an image with three bands selected
automatically. If the image was not opened previously, it will
open with the first three bands selected automatically. If the
image was opened previously by clicking Open, it will open
using the bands that you selected the last time you opened the
image.
• Quick Open & Close to open the image as if you clicked Quick
Open and then have the Open Photo window close
automatically.
Next step in your project . . .
See “Collecting Control Points and Computing the Math Models” on
page 33.
Supported Satellite Formats
The following is a list of supported input formats for OrthoEngine:
• NITF format with or without rational function
• For color data stored in separate files, you can point to any Tiff file.
Channel 1, 2, 3, and 4 correspond to red, green (grn), blue (blu) and
near infrared (nir) data.
IRS (EOSAT) :
• IRS full scene data
• ORBIT-ORIENTED or MAP-ORIENTED product
Note
This format is not recommended. You should use Super structure format for
highest accuracy.
IRS (Super Structure):
The IRS Super Structure CD provides different levels of processing.
OrthoEngine supports level 0 and level 1 CDs. Level 0 is raw, and level
1 is radiometrically corrected. Other levels are not recommended.
JERS1 (LGSOWG):
• ASAR 1B format
JERS-1 CD provides different levels of processing. We recommend
that you use a georeferenced level or equivalent for highest accuracy.
OrthoEngine only works for descending order images.
ASTER:
LANDSAT 5 (Brazilian):
• ASTER Level 1A and 1B HDF format.
• Full scene with level 4 or 5 processing level
However, we recommend Level 1A to obtain the highest accuracy.
Level 1B is not recommended.
LANDSAT 5 (EOSAT):
ASAR:
• LANDSAT 5 image full scene data
IKONOS:
The IKONOS provides different levels of processing. The following
formats are recommended:
• ORBIT-ORIENTED or MAP-ORIENTED product (ORBITORIENTED is recommended)
• SYSTEMATIC geodetic processing
• GEO product in UTM WGS84 GeoTiff format
18
PCI Geomatics
Supported Satellite Formats
LANDSAT 5/7 (LSGOWG) Canadian CDs:
• Basic product in NITF format
• LANDSAT full scene or sub-scene image data
QUICKBIRD standard product is already corrected using GTOPO30
DEM, therefore, is not recommended. We will re-evaluate the product
when the GTOPO30 DEM correction is no longer applied.
• Level 4 processing (bulk', radiometric, and along scan line geometric
corrections applied)
• Level 5 processing (georeferenced) CD
Note
You should use level 4 CD with supplemental volume for highest accuracy.
RADAR (CEOS) ERS data:
ERS CD provides different levels of processing. We recommend the
georeferenced level for images produced in Canada and the PRI level
produced by ESA.
LANDSAT 5/7 (LSGOWG) ESA CDs:
RADAR (CEOS) RADARSAT:
• Level 5 full scene or quad scene
• SGC (SAR Georeferenced Coarse Resolution)
• SGF (SAR Georeferenced Fine Resolution)
LANDSAT 5 (NLAPS):
• SGX (SAR Georeferenced Extra Fine Resolution)
• NLAPS full scene with level 8 processing level
• SLC (Single Look Complex)
LANDSAT 7 (HDF, TIFF, FAST, NLAPS):
• Full scene with 1G progressing in HDF, Tiff, Fast, or NLAPS format
• 0R or 1R is not recommended because of discontinuity on the image
The header file for HDF is the file that contains "HDF" or "hdf". The
header file for Tiff is the file that contains "TIF" or "tif". The header
file for Fast is the file that contains "HPN", "hpn", "HRF", "hrf",
"HTM" or "htm". The header file for NLAPS is the file that contains
"h1", "h2", or "h3".
• SCN (ScanSAR Narrow Beam Product)
• SCW (ScanSAR Wide Beam Product)
Note
SCN and SCW data is rotated top to bottom for ascending path imagery or
left to right for descending path imagery. Therefore, the upper-left corner of
the image is the north-west corner like the single-look products. If the
imagery is flipped, this action is printed to the terminal and REPORT.
MERIS (ENVISAT)
SPOT 1 to 3 (LGWOWG) Canadian format:
• MERIS 1B format
The Canadian LGSOWG CD provides different levels of processing.
OrthoEngine only supports the level 1 CD. Level 1 is radiometrically
corrected with detector offsets applied.
QUICKBIRD (TIFF, NITF):
QUICKBIRD provides different levels of processing. The following
formats are recommended:
• Basic product in GeoTiff
OrthoEngine User’s Guide
SPOT 1 to 4 (SPOTIMAGE):
The SPOTIMAGE LGSOWG CD provides different levels of
processing. OrthoEngine supports level 0, 1A, and 1B CD. However,
we recommend level 1A for highest accuracy. OrthoEngine also
19
Chapter 3 - Importing and Viewing Images
supports old SPOTIMAGE LGSOWG format and the new CAP-T
format.
SPOT 5 (TIFF):
The SPOTIMAGE provides different levels of processing.
OrthoEngine supports level 1A SPOT 5 Dimap format only.
Note
This is the initial SPOT 5 model support. The model will be improved later
after testing done by Dr. Thierry Toutin at CCRS.
20
PCI Geomatics
CHAPTER
4
Setting Up Camera Calibration and Aerial Photographs
Understanding Camera Calibration Data
Defining Focal Length
The camera calibration data is used to identify and correct the
distortions introduced into the photograph due to the curvature of the
lens, the focal length, and the perspective effects. This information is
used to compute the interior orientation, which is the relationship
between the film and the aircraft.
The Focal Length is the distance between the focal point of the lens and
the film. Entering an incorrect focal length may introduce unwanted
distortions in your project. To enter this compulsory parameter, see
“Entering the Camera Calibration Data” on page 24.
Figure 4.1: Effect of focal length on computed position of the camera
Images taken with a standard photogrammetric aerial camera usually
come with a report that provides data about the camera. If images from
a digital or video camera did not come with a camera calibration report,
the data can be obtained from the camera manufacturer or from the
companies that perform the calibration for standard aerial cameras.
For more information, see:
“Defining Focal Length” on page 21
“Defining Principal Point Offset” on page 22
“Defining Radial Lens Distortion” on page 22
“Defining Decentering Distortion” on page 22
“Defining Photo Scale” on page 23
“Defining Earth Radius” on page 23
“Defining Fiducial Marks” on page 23
“Defining Chip Size and Y Scale Factor” on page 24
21
Chapter 4 - Setting Up Camera Calibration and Aerial Photographs
Defining Principal Point Offset
The Principal Point is the point on the image where a ray of light
travelling perpendicular to the image plane passes through the focal
point of the lens and intersects the film. In a perfectly assembled
camera, the principal point would be where the lines of opposing
fiducial marks on an photograph intersect. However, in most cameras
a slight offset occurs. The perspective effects in the image are radial
about this point. This parameter is optional, but the offsets are usually
specified in the camera calibration report. To enter the Principal Point
Offset, see “Entering the Camera Calibration Data” on page 24.
Defining Radial Lens Distortion
Radial Lens Distortion is the symmetric distortion caused by the lens
due to imperfections in curvature when the lens was ground. In most
cases, the errors introduced by radial lens distortion (around 1 to 2 um)
are much smaller than the scanning resolution of the image (around
25um). Entering the values may significantly increase the processing
time while contributing very little value to the final product. The
values for the Radial Lens Distortion may be provided to you as R0
through R7 coefficients or in tabular format. The equation for the lens
distortion is:
delta r =
R0 + R1*r + R2*r2 + R3*r3 + R4*r4 + R5*r5 + R6*r6+ R7*r7
where:
r = radial distance from the center of the image
R0 to R7 = radial distortion coefficients
If you are using a USGS camera calibration report, the coefficients are
given as K0, K1, K2, K3 and K4, which correspond to R1, R3, R5, and
R7. K4 is discarded since it is usually zero.
The radial lens distortion parameter is optional and the coefficients
may or may not appear in the camera calibration report. To enter the
coefficients, see “Entering the Camera Calibration Data” on page 24.
22
If you have a table of distortion pairs, click Compute From Table in
the Standard Aerial Camera Calibration Information window. In
the Distance Units list, select a unit. Enter a value in the Radial
Distance box and the Radial Distortion box and click Accept. Repeat
this step with each set of distortion pairs. Once you have completed the
table, click Accept at the bottom of the window.
Note
We recommend that you obtain the Radial Distortion values for digital
cameras. Since the manufacturing of digital cameras and their lenses is
often not as precise as that for high-end photogrammetric cameras, the
Radial Distortion tends to be higher.
Defining Decentering Distortion
Decentering Distortion is the non-symmetric distortion due to the
misalignment of the lens elements when the camera is assembled. The
Decentering Distortion values may be provided to you as P1 to P4
coefficients or in tabular format. The equation for decentering
distortion is:
delta x = (1 + P3r2 + P4r4 ...) (P1 (r2+2x2) + 2P2xy)
delta y = (1 + P3r2 + P4r4 ...) (2P1xy + P2(r2+2y2)
where:
x = the x image coordinate of a given image point
y = the y image coordinate of a given image point
Pn = the decentering distortion coefficients
delta x = the distortion of an image point at x and y in the x-axis
delta y = the distortion of an image point at x and y in the y-axis
The decentering distortion parameter is optional and the coefficients
may or may not appear in the camera calibration report. To enter the
distortion, see “Entering the Camera Calibration Data” on page 24.
PCI Geomatics
Understanding Camera Calibration Data
Note
We recommend that you obtain the Decentering Distortion values for digital
cameras. Since the manufacturing of digital cameras and their lenses is
often not as precise as that for high-end photogrammetric cameras, the
Decentering Distortion tends to be higher.
Defining Photo Scale
Photo Scale is the ratio of the size of the objects in the image to the size
of the objects on the ground. This parameter is optional, except when
you want to import GPS/INS observations and use them during the
automatic tie point measurements.
The Photo Scale equation is:
d
f
Scale = --- = --D
H
where:
d = distance in the image
D = distance on the ground
f = focal length
H = height above the ground
To enter the Photo Scale, see “Entering the Camera Calibration Data”
on page 24. Entering the incorrect Photo Scale may cause the
computation of the math model (the bundle adjustment) to fail.
Defining Earth Radius
The Earth Radius is the radius of curvature of the earth at the location
of the project. This parameter is optional since aerial photographs
usually use a large scale (for example, 1:8,000) and the error due to the
earth’s radius is negligible. You only need earth radius correction for
photographs with a scale over 1:20,000.
OrthoEngine User’s Guide
The Earth Radius equation is:
radius = a(1-e2)/(1-e2sin2φ)3/2
where:
φ = mean latitude of the project (based on your GCPs)
a = semi-major axis (from the datum definition)
b = semi-minor axis (from the datum definition)
e = (a2-b2)/a2
To enter the Earth Radius, see “Entering the Camera Calibration Data”
on page 24.
Defining Fiducial Marks
Fiducial marks are small crosses or small V-shaped indents located
precisely on each of the four corners and/or exactly midway along the
four sides of a standard aerial photograph. Images taken with digital or
video cameras do not contain fiducial marks. After you identify the
fiducial marks in your scanned image, OrthoEngine uses the fiducial
marks entered from the camera calibration report to establish an image
coordinate frame.
The fiducial mark coordinates are a compulsory parameter for standard
aerial photographs. To enter the coordinates, see “Entering the Camera
Calibration Data” on page 24.
If you do not have calibrated fiducial coordinates, you can estimate the
reference frame by:
• using a ruler to measure distance between the fiducial marks on the
paper print or diapositive
• using the corners of the exposure (not the corners of the file or paper) as
fiducial marks if you have scanned the entire print
To enter the measurements click Compute from Length in the
Standard Aerial Camera Calibration Information window and type
the measurements in the Top Edge Length, Right Edge Length,
Bottom Edge Length, and Left Edge Length boxes.
23
Chapter 4 - Setting Up Camera Calibration and Aerial Photographs
To collect the fiducial marks in the scanned image, see “Collecting
Fiducial Marks Manually” on page 25.
4. In the Principal Point Offset boxes, type the x and y offsets in
millimeters.
5. Under Chip Information (for digital or video cameras only):
Defining Chip Size and Y Scale Factor
The Chip Size is the physical size of the Charged Coupled Devices
(CCDs) in digital or video cameras. Since the images from digital and
video cameras do not contain fiducial marks, the size of the CCDs is
used to calculate the geometry of the camera. Most cameras have
square sensor cells, but some (especially video cameras) may have
rectangular sensor cells.
The Y Scale Factor is the ratio between the horizontal and the vertical
size of each sensor cell in digital or video cameras. It is used when the
CCD pixels are not square. Using the Chip Size and Y Scale Factor, the
digital or video image is automatically converted into a normalized
square photo coordinate system. The image can then be processed
during the computation of the math model (the bundle adjustment) in
the same way as an image taken with a standard aerial camera.
To enter the Chip Size and Y Scale Factor, see “Entering the Camera
Calibration Data” on page 24.
Entering the Camera Calibration Data
The Standard Aerial Camera Calibration Information window or
the Digital/Video Camera Calibration Information window may
open automatically after completing the Set Projection window. If it
is open, skip to step 3. For more information about camera calibration
data, see “Understanding Camera Calibration Data” on page 21.
• In the Width and Height boxes, type the width and height of the
camera’s CCDs in millimeters.
• In the Y Scale Factor box, type the parameter from the
manufacturer’s specifications or from the camera calibration
report (if available).
6. Under Radial Lens Distortion, type the R0 to R7 values or click No
Distortion if the coefficients are not available.
If you have a table of distortion pairs, click Compute From Table.
In the Distance Units list, select a unit. Enter a value in the Radial
Distance box and the Radial Distortion box and then click Accept.
Repeat this step with each set of distortion pairs. Once you have
completed the table, click Accept at the bottom of the window.
7. Under Decentering Distortion, type the coefficients or click No
Distortion if the coefficients are not available.
8. Under Fiducial Marks (for standard aerial cameras only):
•
Click one of the Position options where the fiducial marks will
be collected.
• In the X and Y boxes, type the x and y coordinates of the fiducial
marks in millimeters.
If you do not have calibrated fiducial coordinates, click Compute
from Length and type your measurements in the Compute
Fiducials window.
To enter the camera calibration data:
9. In the Photo Scale box, type the nominal scale.
1. On the OrthoEngine window in the Processing Step list, select
Project.
10. In the Earth Radius box, type the earth radius in meters (if a notable
curvature of the earth is present over the photograph’s area).
2. Click
11. Click Accept.
the Set Camera Calibration icon.
3. In the Focal Length box, type the focal length in millimeters.
24
PCI Geomatics
Collecting Fiducial Marks Manually
5. Click precisely in the center of the fiducial mark.
Next step in your project . . .
For the next step in your project, see “Importing Images or Photographs into
Your Project” on page 15.
Collecting Fiducial Marks Manually
OrthoEngine links the fiducial mark coordinates entered from the
camera calibration report to the positions that you identify on the
scanned image. See “Entering the Camera Calibration Data” on
page 24 to enter the position of the fiducial marks from the calibration
report. You must identify the fiducial marks in every image. Images
from digital or video cameras do not contain fiducial marks.
6. In the Fiducial Mark Collection window, click Set beside the
fiducial mark location corresponding to the mark that you clicked in the
opened image.
Ignore the orientation of the scanned image. Follow the locations of
the fiducial marks as they appear in the image on the screen. For
example, if you clicked in the upper left corner of the image on your
screen to collect the fiducial mark, then you click Set beside Top
Left in the Fiducial Mark Collection window. OrthoEngine
automatically adjusts its parameters to account for the orientation of
the scanned image relative to the orientation of the camera.
If the image is open, click
the Collect fiducial info icon on the
OrthoEngine window and continue with step 3.
Tip
If you are working in a project with a large volume of images, we
recommend that you enter the fiducial marks and ground control points for
a limited number of images (up to five), complete the bundle adjustment for
the math model, and then check for errors before continuing. It is easier to
locate bad points on a few images than over the entire project.
To manually collect fiducial marks:
1. On the OrthoEngine window in the Processing Step list, select
Data Input.
2. Open an uncorrected image. For more information, see “Opening
Images” on page 17.
The Fiducial Mark Collection window opens automatically.
3. Click the approximate location of a fiducial mark in the opened image.
7.
Click the Zoom Out button to reduce the magnification and repeat the
process to collect the remaining fiducial marks.
8. Under Errors, OrthoEngine compares the computed fiducial mark
positions based on the measurements taken from the screen with the
fiducial information that you entered from the camera calibration
report. Click Clear beside any fiducial marks where the error is not
acceptable and repeat the collection process.
The error should be less than one pixel, unless the image is scanned at
a very high resolution. Large errors may indicate that either the
coordinates from the camera calibration report were entered
incorrectly or the fiducial mark was collected incorrectly from the
scanned image.
9. In the Calibration Edge list, select the position of the data strip as it
appears in the image on the screen. Since the camera calibration
4. Click the Zoom In button until you can see the fiducial mark clearly.
OrthoEngine User’s Guide
25
Chapter 4 - Setting Up Camera Calibration and Aerial Photographs
normally assumes that the data strip is on the left, OrthoEngine
compensates for the difference automatically.
2. Manually collect the fiducial marks for one image. For information,
see “Collecting Fiducial Marks Manually” on page 25.
3. When you are satisfied with the results for that image under Errors,
click Auto Fiducial Collection.
4. In the Question window asking, “Do you want to overwrite photos
with fiducial marks?”, click:
• Yes to use the pattern matching on all fiducial marks on all
images.
If your scanned image does not include the data strip, orient the
original diapositive or print to match the image on screen and deduce
where the data strip would be on screen.
• No to use the pattern matching only on the images without
measured fiducial marks.
5. After the Progress Monitor closes, click Accept.
10. When you are satisfied with the results, click Accept.
Once you identify the fiducial marks in your scanned image, the
parameters from the camera calibration report are used during the
bundle adjustment and product generation to compensate for the
distortions introduced by the camera.
See also “Collecting Fiducial Marks Automatically” on page 26 and
“Understanding Exterior Orientation”.
Next step in your project . . .
See “Understanding Ground Control Points” on page 33.
Collecting Fiducial Marks Automatically
After collecting the fiducial marks manually for one of your images,
OrthoEngine can use automated pattern matching to automatically
collect the fiducial marks for the rest of your images in the project.
To automatically collect fiducial marks:
1. Import all the images for your project. For more information, see
.“Importing Images or Photographs into Your Project” on page 15.
26
You can verify the accuracy of the fiducial mark collection under
Errors in the Fiducial Mark Collection window or you can view the
fiducial.rpt report in the folder where the project is saved.
Next step in your project . . .
See “Understanding Ground Control Points” on page 33.
Understanding Exterior Orientation
Exterior orientation represents a transformation from the ground
coordinate system to the photo coordinate system. In most projects
exterior orientation is computed from ground control points (GCPs)
and tie points. Adding estimated or observed exterior orientation to
your project reduces the amount of GCPs that you need, it helps to
automate the tie point collection, and it decreases the time needed to
set up the project, because it provides an approximate location for the
images.
The exterior orientation is the position and orientation of the camera
when the image was taken. In other words, it is the relationship
between the ground and the image. Many photogrammetric cameras
are equipped with onboard Global Positioning Systems (GPS) and
PCI Geomatics
Understanding Exterior Orientation
sometimes with Inertial Navigation Systems (INS) or Inertial
Measurement Unit (IMU) as well. These systems collect the exterior
orientation directly on the plane.
value is about 90 degrees, you will need to rotate the kappa value by 90 degrees (90 degrees is equivalent to 100 gradients).
For Reference
Tip
For more information about GPS/INS, see “Integrated Sensor Orientation
Test Report and Workshop Proceedings” at http://www.ipi.uni-hannover.de/
html/publikationen/special/oeepe_publ_no43.htm.
The position of the camera means the x, y, and z location of the
camera’s focal point measured in a right-handed mapping coordinate
system. The orientation of the camera is given by omega (the rotation
about the x axis), phi (the rotation about the y axis), and kappa (the
rotation about the z axis) as shown in Figure 4.2. The x, y, and z
coordinates and the omega, phi, and kappa angles are referred to
collectively as the six parameters of exterior orientation.
Elements of Photogrammetry Third Edition by Paul R. Wolf
Digital Photogrammetry: An Addendum to the Manual of Photogrammetry,
published by American Society for Photogrammetry & Remote Sensing
Figure 4.2: Understanding Omega, Phi, and Kappa
You can import the GPS/INS data (navigation solution) as direct
observations of the exterior orientation. GPS/INS data from any sensor
system (including POS/EO from Applanix) that uses omega, phi, and
kappa is compatible with OrthoEngine. Use the GPS/INS data alone as
User Input and accept them as correct or use ground control points
and/or tie points to refine the GPS and INS results. For more
information, see “Starting a Project Using the Aerial Photography
Math Model” on page 9. If you have an existing triangulation solution
for the project, you can import it as a known solution for the exterior
orientation. It allows you to skip GCP and tie point collection.
GPS/INS and triangulation data is usually already calibrated to the
orientation of the images, but may require kappa rotations in some
cases. It is quite common for some formats, such as Albany and Pat-B,
to have kappa values rotated due to different flight lines. You should
rotate the kappa value according to the scanning direction. Kappa is the
counter-clockwise angle required to rotate from map north to photo
north (up). For example, a scanned photo with north up should have
kappa near 0 degrees, while a photo with north right should have kappa
near 90 degrees. If a photo is scanned with north up and the input kappa
OrthoEngine User’s Guide
27
Chapter 4 - Setting Up Camera Calibration and Aerial Photographs
Importing GPS/INS or Exterior Orientation
Data from a Text File
OrthoEngine will only extract the entries from the text file that match
the photo IDs from the entries in the project. For more information about
exterior orientation, see “Understanding Exterior Orientation” on page 26.
To import GPS/INS or Exterior Orientation:
1. On the OrthoEngine window in the Processing Step list, select
Data Input.
2. Click
the Import GPS/INS or exterior orientation data
from file icon.
If you chose Compute from GCPs and Tie Points when you started
your project, the Import GPS/INS Data from Text File window
opens. If you chose User Input when you started your project, the
Import Exterior Orientation Data from Text File window
opens.
3. In the File Format list, click the string that represents the layout of the
data in the text file.
For example, the string PhotoID X Y Z represents the layout. The first
column is the photo ID number, the second column is the x
coordinate, the third column is the y coordinate, and the fourth
column is the z coordinate. Estimated errors in the coordinates and
the orientation are represented by values; such as eX, eY, eZ, and so
on. A forward slash (/) represents a new line.
4. In Angle Unit, select the unit for the orientation angles that are used in
the text file. Click:
• Degree if the file expresses the angles in degrees. If a circle is
divided along its radius into 360 equal parts, a degree is the angle
between two adjacent radii measured at the center of the circle.
• Radian if the file expresses the angles in radians. A radian is a
unit used to measure angles where 2 pi radians equals the 360
28
degrees in a circle. Therefore, one radian equals approximately
57.29577951 degrees.
• Grads if the file expresses the angles in grads. A grad is a unit
used to measure angles where 400 grads equals the 360 degrees in
a circle. Therefore, a 90-degree right angle equals 100 grads.
• DMS if the file expresses the angles in Degrees Minutes Seconds.
This angle unit is only available on the Import Exterior
Orientation Data from Text File window. DMS is a unit used
to measure angles where a degree is divided into equal parts. A
circle contains 360 degrees. Each degree is divided into 60
sections called minutes. Each minute is also divided into 60
sections, which are called seconds. Therefore, each angle is
described by a number of degrees, minutes, and seconds.
5. In Accuracy, enter the estimated error for orientation parameters in
the X, Y, Z, Omega, Phi, and Kappa boxes, if available. Accuracy
only appears on the Import GPS/INS Data from Text File
window.
The data set or GPS/INS sensors usually contain the estimated
accuracies. The estimated error values are used to automatically
weight the exterior orientation data with GCPs and tie points during
the computation of the math model. The units are the same as the
input file.
6. In the Text File box, type the path or click Browse to select the text
file that contains the orientation parameters.
7. Under Projection, type the projection string for the source data (for
example, UTM 17 T D000) in the text box beside the Earth Model
button or click Set Input Projection based on Output Projection
if your input projection is the same as your output projection.
If you do not know the projection string:
• Select a projection type from the Input Projection list.
(For UTM, State Plane Coordinate Systems (SPCS), or Other
projection types, additional windows may open automatically for
you to select the parameters to define the projection or click
PCI Geomatics
Entering the Exterior Orientation Manually
More to open these windows. Select the parameters and click
Accept.)
• Click Earth Model.
• Click either the Datum or Ellipsoid tab.
• Click a datum or an ellipsoid.
• Click Accept.
8. The table under Extracted Data shows the contents of the exterior
orientation extracted from the source text file. If you need to rotate
the Kappa value, select the photographs under Extracted Data or
select Rotate all photos to rotate all the photographs under
Extracted Data. In Rotate Kappa, click a rotation button to rotate
the photograph(s) as required. Rotate Kappa only appears on the
Import Exterior Orientation Data from Text File window.
9. Click Apply.
Entering the Exterior Orientation
Manually
For more information about exterior orientation, see “Understanding
Exterior Orientation” on page 26.
To enter the Exterior Orientation manually:
1. On the OrthoEngine window in the Processing Step list, select
Data Input.
2. Click
the Enter GPS/INS or exterior orientation data
manually icon.
If you chose Compute from GCPs and Tie Points when you started
your project, the Input GPS/INS Data Manually window opens. If
you chose User Input when you started your project, the Input
Exterior Orientation Data Manually window opens.
button or click Set Input Projection based on Output Projection
if your input projection is the same as your output projection.
If you do not know the projection string:
• Select a projection type from the Input Projection list.
(For UTM, State Plane Coordinate Systems (SPCS), or Other
projection types, additional windows may open automatically for
you to select the parameters to define the projection or click
More to open these windows. Select the parameters and click
Accept.)
• Click Earth Model.
• Click either the Datum or Ellipsoid tab.
• Click a datum or an ellipsoid.
• Click Accept.
4. Under Unit, click the unit for the orientation angles.
5. Under Photos, select a photograph.
The exterior orientation parameters previously set for the photograph,
if any, are displayed under Exterior Orientation Parameters.
6. Under Exterior Orientation Parameters, type the exterior orientation
parameters of the selected photograph into the X, Y, Z, Omega, Phi,
and Kappa boxes.
7. On the Input GPS/INS Data Manually window in the +/- boxes
beside the X, Y, Z, Omega, Phi, and Kappa boxes, type the
estimated error for the orientation parameters, if available.
The data set or GPS/INS sensors usually contain the estimated
accuracies. The estimated error values are used to automatically
weight the exterior orientation data with GCPs and tie points during
the computation of the math model. The units are the same as the
input file.
3. Under Projection, type the projection string for the source data (for
example, UTM 17 T D000) in the text box beside the Earth Model
OrthoEngine User’s Guide
29
Chapter 4 - Setting Up Camera Calibration and Aerial Photographs
After typing in the Omega, Phi and Kappa values, you can use the
Unit options to convert the values between Degrees and Radians for
comparison. OrthoEngine stores these values in degrees internally.
8. Click Accept.
9. Repeat steps 5 to 7 until all the photographs are set.
10. Click Close.
Changing Photo Orientation
Change Photo Orientation does not apply to digital or video images
since they do not contain data strips or fiducial marks. Although it is
not necessary to position the aerial photographs in a specific manner,
you may find it easier to work with your photographs when they appear
on the screen in a particular fashion:
• You can rotate your photographs until the tops are closest to North so
they correspond to the map coordinate reference frame, which makes
collecting ground control points (GCPs) easier.
• You can rotate the photographs so that the along-strip overlap is along a
left to right axis, which makes tie point collection easier and is
convenient for projects that require stereo overlap such as digital
elevation model (DEM) extraction.
To change the Photo Orientation:
1. On the OrthoEngine window in the Processing Step list, select
Data Input.
2. Click
the Change photo orientation icon.
3. Under Location for Rotated Photos, click:
• Same directory as Input Photo to save your rotated
photographs in the same folder as the raw photographs.
• All Output to this Directory and type the path in the box
underneath or click Browse to select a folder.
30
4. Select Delete Input Photo when complete to delete the raw
photographs from the disk.
5. Under List of Photos to Rotate in the Rotate/Flip column, click the
boxes corresponding to the photographs that you want to rotate or flip
or click All to select all the available photos.
The Input File column shows the filenames of the raw photographs.
The Output File column shows the filenames that will be used for
the rotated photographs. By default, the output filename is the input
filename appended with “_R” with the same extension. You can
change the filename by clicking the output filename and typing the
name of your choice.
6. Under Rotate/Flip Operation, click a rotate button and/or a flip
button to achieve the direction of your choice.
7. In Working Cache, type the amount of RAM that you allocate for this
process.
You can adjust the Working Cache to limit the amount of memory
used to allow other tasks to be completed. Due to disk cache
requirements, rotations of +90 and -90 degrees take much longer than
180 degree rotations.
8. Under Processing Start Time, click Start Now or Start at (hh:mm)
and set the time when you want the operation to begin (within the next
24 hours).
9. Click Start Rotation.
When the photograph is rotated and/or flipped, the photograph’s
GCPs, tie points, clip area, fiducial marks, and calibration edge are
modified to match the new orientation.
Defining a Clip Region
The Clip Region identifies an area of interest from an uncorrected
satellite or aerial images for use as an input window. OrthoEngine will
only process the area inside the clip region, which results in smaller
PCI Geomatics
Defining a Clip Region
files and faster processing. You can also use it to remove the data strip
and fiducial marks from photographs.
To define a clip region:
1. On the OrthoEngine window in the Processing Step list, select
Data Input.
2. If the Open Photo window is not open, click
existing photo icon.
the Open new or
3. In the Open Photo window, select an image.
4. Click Open.
5. Click Zoom to Overview.
6. Click
the Define Clip Region icon.
7. In the window with the open image, click on the red guidelines and
drag to frame the area that you want or in the Define Clip Region
window type the image coordinates of the upper left corner in the
Upper Left Corner X box and the Upper Left Corner Y box. To
determine the clip region size, type the number of pixels in the X Size
box and the number of lines in the Y Size box. To move the Clip
Region, click inside the region and drag it to its new position.
8. Click Done.
OrthoEngine User’s Guide
31
Chapter 4 - Setting Up Camera Calibration and Aerial Photographs
32
PCI Geomatics
CHAPTER
5
Collecting Control Points and Computing the Math Models
Understanding Ground Control Points
A ground control point (GCP) is feature that you can clearly identify in
the raw image for which you have a known ground coordinate. Ground
coordinates can come from a variety of sources such as the Global
Positioning System (GPS), ground surveys, existing geocoded images,
vectors or Geographic Information Systems (GIS), topographic maps,
chip databases, or by using photogrammetric processes to extend the
number of GCPs in your images. The GCPs are used to determine the
relationship between the raw image and the ground by associating the
pixels (P) and lines (L) in the image to the x, y, and z coordinates on
the ground.
Figure 5.1: The relationship between the ground coordinate system and the
image coordinate system
Next step in your project . . .
See one of the following:
“Collecting Ground Control Points Manually” on page 36, “Collecting
Ground Control Points from a Geocoded Image” on page 37, “Collecting
Ground Control Points from Vectors” on page 39, “Collecting Ground
Control Points from a Chip Database Manually” on page 40, “Collecting
Ground Control Points from a Chip Database Automatically” on page 43, or
“Collecting Ground Control Points from a Tablet” on page 47.
33
Chapter 5 - Collecting Control Points and Computing the Math Models
Choosing Good Ground Control Points
The quality of your ground control points (GCPs) directly affects the
accuracy of your math model, and that, in turn, determines the outcome
of your project. When you collect the GCPs:
Table 1: Minimum Number of GCPs
Minimum
GCPs
Recommended
3 or 4 per
project
3 per photo for highest
accuracy
4 per image
6 per image
6 per image
6 per image
8 per image
depends on GCP quality
depends on GCP quality
6 to 8 per image
10 to 12 per image
10 to 12 per image
RADARSAT, ERS, JERS,
ASAR, EROS
8 per image
10 to 12 per image
RADARSAT with the
RADARSAT specific model
GCPs
optional
improve accuracy with 1
or 2 GCPs
If Computed from GCPs
5 per
image*
19 per image*
If Extracted from Image File
none
optional,
for IKONOS Ortho Kit
improve accuracy with 1
or more GCPs
3 per image
more than the minimum
will average out errors
introduced by inaccurate
GCPs or terrain
variations
Math Model
Aerial Photography
• Choose features that you can identify accurately at the resolution of the
raw image.
• Select features that are close to the ground. Features that rise above the
ground, such as buildings, may appear to lean in the image. Therefore, a
point collected from the top of the feature may be displaced from the
actual ground coordinate.
• Avoid using shadows as GCPs. Although shadows may be easy to see
in the image, they are not permanent and can move from one image to
another.
• Beware of selecting common or repetitive features as GCPs such as
parking lots or lines on a highway. When you try to identify the feature
in the image, it may be difficult to select the right one.
• Identify the features in the raw image that you want as ground control
before collecting GCP coordinates in the field using a GPS or ground
survey.
• Collect GCPs from a variety of elevations in a wide distribution over
the image and the project.
• Collect GCPs in an area of overlap between two or more images
when possible. The same ground coordinate collected in multiple
images helps to produce a more accurate model.
Satellite Orbital:
Optical
SPOT 1 TO 4
SPOT 5
IRS, ASTER, EOC
LANDSAT, QUICKBIRD
IKONOS
SAR images
Rational Functions:
Thin Plate Spline
Collecting the Right Number of Ground Control
Points
The following is the minimum number of ground control points (GCPs)
to collect, but we recommend that you collect more than the minimum
to ensure accuracy. However, collecting over 20 GCPs per image does
not significantly improve the accuracy for most math models. To
improve the accuracy, collect GCPs evenly throughout the image at a
variety of elevations and in areas where images overlap. Also, the
quality of the GCPs impacts the number needed to ensure accuracy.
34
PCI Geomatics
Determining the Right Combination of Ground Control Points and Tie Points for the Satellite Math Model
Table 1: Minimum Number of GCPs
Math Model
Minimum
GCPs
Polynomial:
First-order
4 per image
Second-order
7 per image
Third-order
11 per
image
Fourth-order
16 per
image
Fifth-order
22 per
image
can use tie points with elevation to reduce the minimum required GCPs
for each image.
Recommended
more than the minimum
will average out errors
introduced by inaccurate
GCPs
*Depends on the number of coefficients that you want to use, see
“Understanding the Rational Functions Math Model” on page 6.
Determining the Right Combination of
Ground Control Points and Tie Points for
the Satellite Math Model
When the viewing angle difference between the images is less than 7
degrees, meaning a base to height (B/H) ratio less than 0.1 to 0.15, you
should collect the minimum required ground control points (GCPs) for
each image in your project. In this case, you should not use tie points,
tie points with elevation, or even stereo GCPs. These points become
mathematically useless due to the same-side weak stereo intersection.
If you are co-registering two scenes from a single sensor, such as a
panchromatic image and a multispectral image of the same scene, do
not use tie points to relate the images. Use the same GCPs on both
scenes. Collecting the same GCPs on adjacent images can also improve
the math model by improving the B/H ratio.
When the viewing angle difference between the images is between 7
and 30 degrees, meaning a B/H ratio between 0.1 to 0.15 and 0.6, you
OrthoEngine User’s Guide
When the viewing angle difference between the images is more than 30
degrees, meaning a B/H ratio more than 0.6, you can use tie points to
extend the ground control. If you use tie points with elevation, you can
reduce the minimum required GCPs for each image.
For example, if you have stereo left and right SPOT images, you can
collect two GCPs on the left image and two GCPs on the right image.
With tie points with or without elevation in the overlap, you can obtain
a geometric model.
Using Auto Locate
The Auto Locate feature appears on the GCP Collection windows, the
Tie Point Collection window, and the Elevation Match Point
window. It is a tool to help you speed up the collection process.
OrthoEngine can estimate the position of the point by using an
automatic correlation method once it has enough information to
calculate the math model. Therefore, the project must have ephemeris
data for satellite imagery, GPS/INS data for aerial photography, a
minimum number of GCPs, or three tie points per image for Auto
Locate to work. You should verify the estimated positions and adjust
them, if necessary, before accepting them.
The cursor will be placed automatically on the pixel and line position of
the selected point in all the open images at a default zoom level when
Auto Locate is selected and you:
• Select an existing point in a GCP Collection window.
• Type the elevation and coordinates under Georeferenced Position in a
GCP Collection window.
• Accept a new tie point in the Tie Point Collection window.
• Accept a new elevation match point in the Elevation Match Point
Collection window.
35
Chapter 5 - Collecting Control Points and Computing the Math Models
Using Bundle Update
The Bundle Update feature appears on the GCP Collection windows
and the Tie Point Collection window when you are creating a project
using a rigorous model. When you select Bundle Update,
OrthoEngine performs the bundle adjustment every time you add a
point to the project. This can help you determine whether the point that
you collected is good enough for your project.
For more information, see “Understanding the Bundle Adjustment for
Rigorous Math Models” on page 55 and “Troubleshooting the Math
Model Solution” on page 56.
Collecting Ground Control Points
Manually
If you have several raw images open, you will notice that one image
resides in a viewer labelled Working while the others are labelled
Reference. The GCP Collection window collects and displays the
GCPs from the image in the Working viewer only. Click the
Reference button to switch the viewer to Working. You can collect
the same GCP in each image by clicking Reference in a viewer,
collecting the GCP, and then repeating the process for each image.
Tip
If you are working in a project with a large volume of images, we
recommend that you enter the fiducial marks and ground control points for
a limited number of images (up to five), complete the bundle adjustment for
the math model, and then check for errors before continuing. It is easier to
locate bad points on a few images than over the entire project.
To collect ground control points manually:
1. On the OrthoEngine window in the Processing Step list, select
GCP Collection.
2. Click
36
the Open new or existing photo icon to open an image.
For information how to open an image, see “Opening Images” on
page 17.
3. On the OrthoEngine window, click
Manually icon.
the Collect GCPs
4. On the GCP Collection window, the Point ID is generated
automatically. You can type a new label in the Point ID box, however,
all points (ground control points, check points, tie points, and elevation
match points) in the image must have unique labels. You can use the
same Point ID for the same GCP in the overlap areas of different
images.
5. In the list below the Point ID box, click:
• Ground Control Point (GCP) to use the GCP to calculate the
math model.
• Check Point (CP) to check the accuracy of the math model. For
more information, see “Troubleshooting the Math Model
Solution” on page 56.
6. You can select Auto Locate and/or Bundle Update to aid with
collection. For more information, see “Using Auto Locate” on page 35
and “Using Bundle Update” on page 36.
7. On the GCP Collection window under Auxiliary Information, you
may have additional features available to you depending on the math
model that you selected:
• If you chose the Rational Function math model, you can select in
the No. of Coefficients list the number of coefficients you want
to use to calculate the math model. For more information, see
“Understanding the Rational Functions Math Model” on page 6.
• If you chose the Polynomial math model, you can select in the
Polynomial Order list which polynomial that you want to use to
calculate the math model. For more information, see
“Understanding the Polynomial Math Model” on page 7.
8. Under Georeferenced Position in the Elev box, type the elevation of
the GCP or you can use a digital elevation model (DEM) to determine
PCI Geomatics
Collecting Ground Control Points from a Geocoded Image
the elevation of your GCPs, see “Using a Digital Elevation Model to
Set Ground Control Point Elevation” on page 51.
9. In the Easting box and the Northing box, type the ground coordinate
of the GCP in the projection shown beside Georeferenced Position.
Next step in your project . . .
For projects using the Aerial Photography or Satellite Orbital math models,
see “Collecting Tie Points Manually” on page 52. For other projects, see
“Understanding the Solution for Simple Math Models” on page 56.
Collecting Ground Control Points from a
Geocoded Image
10. In the +/- boxes beside the Elev box, the Easting box, and the
Northing box, type the estimated error for each.
11. At a zoom level where you can see the detail in the raw image, position
the cursor precisely on the feature that you will use as a GCP and then
click Use Point.
The pixel and line coordinates from the raw image appear in the GCP
Collection window under Photo Position or Image Position.
12. Click Accept.
You can use existing geocoded images as a source for ground control
points (GCPs). By matching the coordinates of points in the geocoded
image to pixel and line coordinates in the raw image, you can collect
as many GCPs as you want.
If you have several raw images open, you will notice that one image
resides in a viewer labelled Working while the others are labelled
Reference. The GCP Collection window collects and displays the
GCPs from the image in the Working viewer only. Click the
Reference button to switch the viewer to Working. You can collect
the same GCP in each image by clicking Reference in a viewer,
collecting the GCP, and then repeating the process for each image.
The GCP is added to the Accepted Points table.
Tip
You can edit the error estimate in the +/- boxes under Image Position to
correspond to your ability to precisely identify a feature in the image. For
example, if you use coarse imagery, you can probably only measure to the
closest pixel. If you use imagery that was compressed or poorly scanned,
you may only be able to measure to the closest two pixels. Even if you
identify a GCP to the closest pixel, the coordinate may only be accurate to
so many meters.
Tip
If you are working in a project with a large volume of images, we
recommend that you enter the fiducial marks and ground control points for
a limited number of images (up to five), complete the bundle adjustment for
the math model, and then check for errors before continuing. It is easier to
locate bad points on a few images than over the entire project.
To collect ground control points from a geocoded image:
1. On the OrthoEngine window in the Processing Step list, select
GCP Collection.
2. Click
OrthoEngine User’s Guide
the Open new or existing photo icon to open an image.
37
Chapter 5 - Collecting Control Points and Computing the Math Models
For information how to open an image, see “Opening Images” on
page 17.
3. On the OrthoEngine window, click
Geocoded Image icon.
the Collect GCPs from
4. On the GCP Collection window, the Point ID is generated
automatically. You can type a new label in the Point ID box, however,
all points (ground control points, check points, tie points, and elevation
match points) in the image must have unique labels.
5. In the list below the Point ID box, click:
• Ground Control Point (GCP) to use the GCP to calculate the
math model.
10. At a zoom level where you can see the detail in the geocoded image,
position the cursor precisely on the feature that you will use as a ground
control point (GCP) and click Use Point.
The geocoded Easting and Northing coordinates transfer to the GCP
Collection window.
11. On the GCP Collection window under Georeferenced Position in
the Elev box, type the elevation of the GCP or you can use a digital
elevation model (DEM) to determine the elevation of your GCPs, see
“Using a Digital Elevation Model to Set Ground Control Point
Elevation” on page 51.
12. In the +/- boxes beside the Elev box, the Easting box, and the
Northing box, type the estimated error for each.
• Check Point (CP) to check the accuracy of the math model. For
more information, see “Troubleshooting the Math Model
Solution” on page 56.
6. You can select Auto Locate and/or Bundle Update to aid with
collection. For more information, see “Using Auto Locate” on page 35
and “Using Bundle Update” on page 36.
7. Under Auxiliary Information, you may have additional features
available to you depending on the math model that you selected:
• If you chose the Rational Function math model, you can select in
the No. of Coefficients list the number of coefficients you want
to use to calculate the math model. For more information, see
“Understanding the Rational Functions Math Model” on page 6.
• If you chose the Polynomial math model, you can select in the
Polynomial Order list which polynomial that you want to use in
your project. For more information, see “Understanding the
Polynomial Math Model” on page 7.
8. Under Auxiliary Information, click Load.
9. In the Database File Selection window, select the geocoded image
file. Click Open.
The geocoded image opens in a window.
38
13. At a zoom level where you can see the detail in the raw image, position
the cursor precisely on the feature that you will use as a GCP and click
Use Point.
The pixel and line coordinates from the raw image appear in the GCP
Collection window under Photo Position or Image Position.
14. Click Accept.
The GCP is added to the Accepted Points table.
Tip
You can edit the error estimate in the +/- boxes under Image Position to
correspond to your ability to precisely identify a feature in the image. For
example, if you use coarse imagery, you can probably only measure to the
closest pixel. If you use imagery that was compressed or poorly scanned,
you may only be able to measure to the closest two pixels. Even if you
PCI Geomatics
Collecting Ground Control Points from Vectors
identify a GCP to the closest pixel, the coordinate may only be accurate to
so many meters.
Next step in your project . . .
For projects using the Aerial Photography or Satellite Orbital math models,
see “Collecting Tie Points Manually” on page 52. For other projects, see
“Understanding the Solution for Simple Math Models” on page 56.
Collecting Ground Control Points from
Vectors
You can use existing vectors as a source for ground control points
(GCPs). By matching the coordinates of points in the vector file to
pixel and line coordinates in the raw image, you can collect as many
GCPs as you want.
If you have several raw images open, you will notice that one image
resides in a viewer labelled Working while the others are labelled
Reference. The GCP Collection window collects and displays the
GCPs from the image in the Working viewer only. Click the
Reference button to switch the viewer to Working. You can collect
the same GCP in each image by clicking Reference in a viewer,
collecting the GCP, and then repeating the process for each image.
Tip
If you are working in a project with a large volume of images, we
recommend that you enter the fiducial marks and ground control points for
a limited number of images (up to five), complete the bundle adjustment for
the math model, and then check for errors before continuing. It is easier to
locate bad points on a few images than over the entire project.
To collect ground control points from vectors:
1. On the OrthoEngine window in the Processing Step list, select
GCP Collection.
2. Click
the Open new or existing photo icon to open an image.
For information how to open an image, see “Opening Images” on
page 17.
3. On the OrthoEngine window, click
Vectors icon.
the Collect GCPs from
4. On the GCP Collection window, the Point ID is generated
automatically. You can type a new label in the Point ID box, however,
all points (ground control points, check points, tie points, and elevation
match points) in the image must have unique labels.
5. In the list below the Point ID box, click:
• Ground Control Point (GCP) to use the GCP to calculate the
math model.
• Check Point (CP) to check the accuracy of the math model. For
more information, see “Troubleshooting the Math Model
Solution” on page 56.
6. You can select Auto Locate and/or Bundle Update to aid with
collection. For more information, see “Using Auto Locate” on page 35
and “Using Bundle Update” on page 36.
7. Under Auxiliary Information, you may have additional features
available to you depending on the math model that you selected:
• If you chose the Rational Function math model, you can select in
the No. of Coefficients list the number of coefficients you want
to use to calculate the math model. For more information, see
“Understanding the Rational Functions Math Model” on page 6.
• If you chose the Polynomial math model, you can select in the
Polynomial Order list which polynomial that you want to use in
your project. For more information, see “Understanding the
Polynomial Math Model” on page 7.
OrthoEngine User’s Guide
39
Chapter 5 - Collecting Control Points and Computing the Math Models
8. Under Auxiliary Information, click Load.
9. In the Database File Selection window, select the vector file. Click
Open.
10. In the File window, select the database vector segment and click Load
or Load & Close. If you want to choose multiple layers, select a
segment and click Load for each layer.
11. At a zoom level where you can see the detail in the Vector File
window, position the cursor precisely on the feature that you will use as
a ground control point (GCP) and click Use Point.
The GCP is added to the Accepted Points table.
Tip
You can edit the error estimate in the +/- boxes under Image Position to
correspond to your ability to precisely identify a feature in the image. For
example, if you use coarse imagery, you can probably only measure to the
closest pixel. If you use imagery that was compressed or poorly scanned,
you may only be able to measure to the closest two pixels. Even if you
identify a GCP to the closest pixel, the coordinate may only be accurate to
so many meters.
The geocoded Easting and Northing coordinates transfer to the GCP
Collection window.
12. On the GCP Collection window under Georeferenced Position in
the Elev box, type the elevation of the GCP or you can use a digital
elevation model (DEM) to determine the elevation of your GCPs, see
“Using a Digital Elevation Model to Set Ground Control Point
Elevation” on page 51.
13. In the +/- boxes beside the Elev box, the Easting box, and the
Northing box, type the estimated error for each.
Next step in your project . . .
For projects using the Aerial Photography or Satellite Orbital math models,
see “Collecting Tie Points Manually” on page 52. For other projects, see
“Understanding the Solution for Simple Math Models” on page 56.
Collecting Ground Control Points from a
Chip Database Manually
A chip database is a compilation of individual image samples, usually
measuring 256 pixels by 256 pixels or smaller. Each image sample
contains an accurate geocoded location and metadata; such as which
sensor it was generated from, the date it was acquired, and the viewing
angle.
14. At a zoom level where you can see the detail in the raw image, position
the cursor precisely on the feature that you will use as a GCP and click
Use Point.
The pixel and line coordinates from the raw image appear in the GCP
Collection window under Photo Position or Image Position.
15. Click Accept.
40
These image samples, called chips, can be used to collect ground
control points (GCPs). You can visually match a feature in the raw
image that you are georeferencing and use the coordinates from the
chip database as a GCP or use the chips to automate the collection of
GCPs. For more information, see “Collecting Ground Control Points
from a Chip Database Automatically” on page 43.
If you have several images open, you will notice that one image resides
in a viewer labelled Working while the others are labelled Reference.
The GCP Collection window collects and displays the GCPs from the
PCI Geomatics
Collecting Ground Control Points from a Chip Database Manually
image in the Working viewer only. Click the Reference button to
switch the viewer to Working. You can collect the same GCP in each
image by clicking Reference in a viewer, collecting the GCP, and then
repeating the process for each image.
Tip
If you are working in a project with a large volume of images, we
recommend that you enter the fiducial marks and ground control points for
a limited number of images (up to five), complete the bundle adjustment for
the math model, and then check for errors before continuing. It is easier to
locate bad points on a few images than over the entire project.
To manually collect ground control points from a chip
database:
1. On the OrthoEngine window in the Processing Step list, select
GCP Collection.
2. Click
the Open new or existing photo icon to open an image.
For information how to open an image, see “Opening Images” on
page 17.
3. On the OrthoEngine window, click
Chip Database icon.
the Collect GCPs from
6. You can select Auto Locate and/or Bundle Update to aid with
collection. For more information, see “Using Auto Locate” on page 35
and “Using Bundle Update” on page 36.
7. On the GCP Collection window under Auxiliary Information, you
may have additional features available to you depending on the math
model that you selected:
• If you chose the Rational Functions math model, you can select in
the No. of Coefficients list the number of coefficients you want
to use to calculate the math model. For more information, see
“Understanding the Rational Functions Math Model” on page 6.
• If you chose the Polynomial math model, you can select in the
Polynomial Order list which polynomial that you want to use in
your project. For more information, see “Understanding the
Polynomial Math Model” on page 7.
8. Under Auxiliary Information, click Load.
9. In the Image Chip Database Selection window, select the chip
database file. Click Open.
10. In the OrthoEngine ChipDatabase window, do one of the
following:
• Click the # button, type the chip ID or chip sequence number, and
then click OK.
• Use the navigation buttons to select chip.
4. On the GCP Collection window, the Point ID is generated
automatically. You can type a new label in the Point ID box, however,
all points (ground control points, check points, tie points, and elevation
match points) in the image must have unique labels.
• Click Search Criteria to narrow the search for chips to a
manageable number of chips and then use the navigation buttons
to select chip. For information about searching the chip database,
see “Searching for Chips in a Database” on page 42.
5. In the list below the Point ID box, click:
• Type the chip ID in the Chip ID box under Chip Information
and then press ENTER.
• Ground Control Point (GCP) to use the GCP to calculate the
math model.
• Check Point (CP) to check the accuracy of the math model. For
more information, see “Troubleshooting the Math Model
Solution” on page 56.
OrthoEngine User’s Guide
Detailed information about the currently selected chip appears under
Chip Information in the OrthoEngine ChipDatabase window. Click
More Info to view detailed header and chip information.
41
Chapter 5 - Collecting Control Points and Computing the Math Models
On the GCP Collection window under Auxiliary Information, you
can click Display Chips to display the geocoded locations of the
chips on your raw image once you have enough information to
calculate the math model.
11. If you want to change the position of the GCP in the chip, select a new
point in the chip image and click Cursor Position is GCP. To change
the GCP location in a chip, the Chip Database must be writeable and
the chip image must be geocoded.
12. Click Use Image Chip in the OrthoEngine ChipDatabase
window.
OrthoEngine attempts to find the corresponding feature in your raw
image and positions the cursor on the feature. The feature’s Easting
and Northing coordinates appear in the GCP Collection window.
13. If the chip does not contain the elevation of the point, you can use
another source. On the GCP Collection window under
Georeferenced Position in the Elev box, type the elevation of the
GCP or you can use a digital elevation model (DEM) to determine the
elevation of your GCPs, see “Using a Digital Elevation Model to Set
Ground Control Point Elevation” on page 51.
14. On the GCP Collection window in the +/- boxes beside the Elev
box, the Easting box, and the Northing box, type the estimated error
for each.
The pixel and line coordinates from the raw image appear in the GCP
Collection window under Image Position or Photo Position.
If you need to enhance the chip image to determine the position of the
ground coordinate, you can use the features available under Image/
DEM Chip. For more information about how to enhance the chip
image, see “Adjusting the View Under Image/DEM Chip” on
page 43.
16. On the GCP Collection window under Georeferenced Position,
click Accept.
The GCP is added to the Accepted Points table.
Tip
You can edit the error estimate in the +/- boxes under Image Position to
correspond to your ability to precisely identify a feature in the image. For
example, if you use coarse imagery, you can probably only measure to the
closest pixel. If you use imagery that was compressed or poorly scanned,
you may only be able to measure to the closest two pixels. Even if you
identify a GCP to the closest pixel, the coordinate may only be accurate to
so many meters.
Next step in your project . . .
For projects using the Aerial Photography or Satellite Orbital math models,
see “Collecting Tie Points Manually” on page 52. For other projects, see
“Understanding the Solution for Simple Math Models” on page 56.
Searching for Chips in a Database
15. At a zoom level where you can see the detail in the raw image, position
the cursor precisely on the feature that you will use as a GCP and click
Use Point.
42
In some cases you might want to narrow the search for chips to a
manageable number of possibilities. By defining the search
parameters, such as the sensor, a range of acquisition dates, or a region
of interest, you can limit the chips that you want to use in the matching
process.
PCI Geomatics
Collecting Ground Control Points from a Chip Database Automatically
To search for a chip:
1. On the OrthoEngine ChipDatabase window, click Search
Criteria.
2. On the Searching Chip Database window, type the parameters that
you want.
3. Click Do Search.
The results of the search are displayed under List of Chips
Matching Search Conditions.
Imagery: Under Image/DEM Chip, select an image channel in the
Imagery list if the chip contains RGB color bands or individual bands
in black and white.
Enhance: See “Understanding the Enhancements” on page 121.
Zoom: See “Using Zoom, ReLoad and Pan” on page 122.
Display: Under Image/DEM Chip, click Chip to view the image
specific to the chip or click Overview to see where the chip is located.
4. If your search was not satisfactory, click Restore Defaults to reset the
window and enter a new set of parameters.
Collecting Ground Control Points from a
Chip Database Automatically
5. For projects using satellite imagery: You can click Default ROI to
Image to use the orbital data from a raw image database to estimate the
parameters under Region of Interest (ROI) within a 50% margin of
error. If you have collected more than three GCPs, OrthoEngine can
compute an affine model to help estimate the ROI parameters within a
25% margin of error.
6. When you are satisfied with your chip selection, click Close.
OrthoEngine can use image correlation to identify the pixel and line
locations in the raw image that correspond to the georeferenced
positions on the chips. For projects using the Satellite Orbital math
model, OrthoEngine can match images from the chip database to your
raw image based on an approximate image model derived from the
orbit information. For projects using the other math models, the
matching process can be accomplished if your project meets one or
more of the following criteria:
Working with the Chip Database
• The exterior orientation of each image was computed based on ground
control points (GCPs) and/or tie points.
To search for chips, see “Searching for Chips in a Database” on
page 42.
• You collected three tie points between every pair of overlapping photos.
For information about tie points, see “Understanding Tie Points” on
page 51.
Changing the Color of the GCP or Cursor in the Chip
• You used a Global Positioning System (GPS) to obtain the x, y, and z
coordinates for each image center, and you estimated the omega, phi,
and kappa rotations, or they were supplied by an Inertial Navigation
System (INS).
In Image/DEM Chip, click Colors to change the color of the ground
control point in the chip and the cursor point in the chip.
Adjusting the View Under Image/DEM Chip
You can make the chip on the screen clearer and easier to interpret
without changing the values in the image file.
OrthoEngine User’s Guide
43
Chapter 5 - Collecting Control Points and Computing the Math Models
To automatically collect ground control points from a chip
database:
1. On the OrthoEngine window in the Processing Step list, select
GCP Collection.
2. On the OrthoEngine window, click
the Automatically
collect GCPs from chip database icon.
A progress indicator displays the percentage of the process
completed. The matches between the chips and the images are
displayed in the Chip ID and Photo ID columns under Chips.
7. To reject matches identified in the Use as GCP column, click in the
Use as GCP column to clear the matches of your choice. You can also
click Use all to select all the matches or click None to clear all of
them.
3. In the Automatic GCP Collection window under Chip Database,
type the path for the chip database or click Browse to select chip
database file.
Click Show Distribution to view how the selected GCPs are
dispersed over the images. The image footprints appear as gray lines,
and the GCPs appear as blue crosshairs.
Search result displays the number of chips in the database. You can
click Search Criteria to limit the number of chips used in the
correlation process. For Information about searching the chip
database, see “Searching for Chips in a Database” on page 42.
For more information about the matching process, see “Changing the
Correlation Parameters for Automatic GCP Collection from a Chip
Database” on page 44.
4. Under Photos in the Use column, click to select or clear the check
marks to select the images that you want to use in the matching
process. Only images with check marks in the Use column will be
used. Click Use all to select all the images under Photos or click
None to clear all of them.
You can only select images with Available listed in the Status
column and Yes in the Model column, which means that the image
has a computed math model.
5. In Match Channel, click the number of the input image channel that
you want to use for the image correlation. Choose the channel that has
the same color band or wavelength as the image chip so the features on
the ground will look the same in the two images. Select Apply to all
Photos if you want to use the same channel for all of the images. To
select a different channel for each image, click the image under Photos
and click the number of the Match Channel that you want to use.
Use a channel other than blue, because the blue band tends to saturate
so it is not as sharp as some of the other bands.
6. Click Match Chips.
44
8. Click the Use as GCPs button to accept the matches identified in the
Use as GCP column as GCPs in your project.
9. Click Print to File if you want to save a record of all matched chips to
a text file.
10. Click Close.
Next step in your project . . .
For projects using the Aerial Photography or Satellite Orbital math models,
see “Collecting Tie Points Manually” on page 52. For other projects, see
“Understanding the Solution for Simple Math Models” on page 56.
Changing the Correlation Parameters for Automatic
GCP Collection from a Chip Database
The correlation between the chip and the raw image is performed in
three progressive levels with each level using a more precise search
area. Matching begins on a low-resolution version of the image to
establish an approximate match, continues with a medium-resolution
PCI Geomatics
Using a Tablet to Collect Ground Control Points
version to refine the match, and ends with a full resolution image to
produce the most precise match possible. Each level produces a
correlation score that appears in the Automatic GCP Collection
window under Chips in the C1, C2, and C3 columns.
The search area is an odd number of pixels forming a square. The last
level using the full resolution version of the image always uses a
search area that is 7-by-7 pixels large.
3. Click OK.
A high correlation score usually means that the identified matching
features are a successful match. Scores lower than the Correlation
Threshold set in the Advanced Option window are shown in red and
are marked as failed.
However, a perfect match may still have a low correlation score since
the chip and the raw image may have been taken at slightly different
resolutions, in different illumination conditions, and with different
sensors. On the contrary, repetitive features, such as lines in a parking
lot, can produce a perfect correlation score because the features look
identical, but the match may be on the wrong feature.
Base your decision to use or reject a match on the correlation scores,
instead of whether the matching is marked passed or failed.
To change the defaults for the minimum correlation score
required for each level:
1. In the Automatic GCP Collection window, click Advanced
Options.
2. In the Advanced Option window under Correlation Threshold,
type a value between zero and one for each of the levels.
3. Click OK.
To change the size of the search area:
1. In the Automatic GCP Collection window, click Advanced
Options.
2. In the Advanced Option window under Correlation Mask
Window size, type the number of pixels to form the width of the
search area for each level.
OrthoEngine User’s Guide
Using a Tablet to Collect Ground Control
Points
By using a digitizing table connected to your computer, you can
transfer the coordinates of a feature from a paper map to your project
and use the coordinates as a ground control point (GCP).
A digitizing table consists of a electronic platform (a tablet) and a
pointing device (a puck). After you connect the digitizing table to your
computer and tape the map to the tablet, you are ready to establish a
reference frame between the tablet, the paper map, and your project.
To set up the reference frame, you have to correlate the georeferenced
map coordinates of a feature in each of the four corners of the paper
map and the x and y coordinates of those features on the tablet. After
the reference frame is set, you can select points on the paper map with
the puck. The georeferenced coordinates will be transferred to your
project for use as GCPs.
Grid Pinning: Since paper maps rarely lie perfectly flat on the tablet’s
surface, you can increase the accuracy in your GCP collection on the
paper map by using Grid Pinning to anchor the reference frame around
each point that you want to use as a GCP. To use Grid Pinning, you
define the size of the frame that you want to use around the point when
you set up the tablet. When you begin collecting GCP coordinates on
the paper map, you select a feature and then select the four points to
form a square around the feature to anchor the reference frame.
Anchoring the reference frame around the feature will help eliminate
the errors due to distortions in the paper map.
45
Chapter 5 - Collecting Control Points and Computing the Math Models
11. Click Connect to Tablet.
Next step in your project . . .
See “Setting Up the Tablet” on page 46.
12. Press a button on the tablet’s puck to verify the communication
between OrthoEngine and the digitizing table. Values should appear in
Tablet Coordinates.
Setting Up the Tablet
13. In Coordinate System, type the projection string (for example,
UTM 17 T D000) in the text box beside the Earth Model button.
To set up the tablet you have to establish communication between the
tablet and the computer and then establish a reference frame between
the tablet, the paper map, and your project.
To set up the tablet:
1. On the OrthoEngine window in the Processing Step list, select
GCP Collection.
2. Click
the Open new or existing photo icon to open an image.
For information how to open an image, see “Opening Images” on
page 17.
3. On the OrthoEngine window, click
tablet icon.
the Collect GCPs by
4. On the GCP Collection window, click Set Up Tablet.
If you do not know the projection string:
• Select a projection type the Coordinate System list.
(For UTM, State Plane Coordinate Systems (SPCS), or Other
projection types, additional windows may open automatically for
you to select the parameters to define the projection or click
More to open these windows. Select the parameters and click
Accept.)
• Click Earth Model.
• Click either the Datum or Ellipsoid tab.
• Click a datum or an ellipsoid.
• Click Accept.
14. In the list below Coordinate System, click Geocoded to enter the
map coordinates in georeferenced units or click Geographic to use
Longitude/Latitude units.
5. In Tablet Setup and Map Tie-down window in the Device box,
type the name of the serial port where you have attached the digitizing
table. For example, serial ports for Windows systems are COM1 or
COM2 and for Unix systems are /dev/ttys1 or /dev/ttya.
15. Select a feature in four corners of the paper map to form a frame
surrounding the area where you want to collect the ground control
points (GCPs). Identify the map coordinates of these four features.
6. In the Tablet type list, click the type of tablet that you are using.
16. At the end of the Up Left row under Tablet Position, click not set.
7. In the Baud Rate list, click the baud rate used by the tablet.
17. On the tablet, move the crosshairs of the puck to the feature in the
upper left corner of the map and press the button to select the point.
8. In the Parity list, click the parity bit setting used by the tablet.
9. In the Data Bits list, click the data bits used by the tablet.
The tablet coordinates (x and y) of the point appear under Tablet
Position.
10. In the Stop Bits list, click the stop bit used by the tablet.
46
PCI Geomatics
Collecting Ground Control Points from a Tablet
18. Type the map coordinates of the point in the Map Eastings box and
Map Northings box in the Up Left row.
19. Follow the same procedures explained in steps 16 to 18 to collect
points for the remaining corners of the map. Type the Map Eastings
and Map Northings coordinates of the map’s upper-right corner in the
Up Right row, the lower-right corner in the Lo Right row, and the
lower-left corner in the Lo Left row. You can also collect a point
within the reference frame in the Other row.
20. You can click Use Grid Pinning to define the size of the frame that
you want to use to anchor the reference frame around each point that
you want to use as a GCP. For more information about Grid Pinning,
see “Using a Tablet to Collect Ground Control Points” on page 45.
After clicking Use Grid Pinning, the Grid Box Definition Panel
opens automatically. Click Geocoded from the list to use
georeferenced units to anchor the reference frame or click
Geographic to use Longitude/Latitude units. Determine the size of
the frame that you want, move the crosshairs of the puck to each
corner of your frame, and press the button to select each point as
required in the Grid Box Definition Panel. When the four points are
set, click Accept.
21. In the Tablet Setup and Map Tie-down window, click Tie-down
Completed.
If you have several images open, you will notice that one image resides
in a viewer labelled Working while the others are labelled Reference.
The GCP Collection window collects and displays the GCPs from the
image in the Working viewer only. Click the Reference button to
switch the viewer to Working. You can collect the same GCP in each
image by clicking Reference in a viewer, collecting the GCP, and then
repeating the process for each image.
Tip
If you are working in a project with a large volume of images, we
recommend that you enter the fiducial marks and ground control points for
a limited number of images (up to five), complete the bundle adjustment for
the math model, and then check for errors before continuing. It is easier to
locate bad points on a few images than over the entire project.
To collect ground control points from a tablet:
1. Set up the digitizing table. For more information, see “Setting Up the
Tablet” on page 46.
2. On the GCP Collection window, the Point ID is generated
automatically. You can type a new label in the Point ID box, however,
all points (ground control points, check points, tie points, and elevation
match points) in the image must have unique labels.
3. In the list below the Point ID box, click:
Next step in your project . . .
See “Collecting Ground Control Points from a Tablet” on page 47.
Collecting Ground Control Points from a
Tablet
After you set up the digitizing table, you can choose any feature that
you can see clearly on the paper map and in the raw image as a ground
control point (GCP).
OrthoEngine User’s Guide
• Ground Control Point (GCP) to use the GCP to calculate the
math model.
• Check Point (CP) to check the accuracy of the math model. For
more information, see “Troubleshooting the Math Model
Solution” on page 56.
4. You can select Auto Locate and/or Bundle Update to aid with
collection. For more information, see “Using Auto Locate” on page 35
and “Using Bundle Update” on page 36.
47
Chapter 5 - Collecting Control Points and Computing the Math Models
5. On the tablet, position the crosshairs of the puck precisely on the
feature on the paper map that you will use as a GCP and press the
button to select the point. If you selected Grid Pinning when you set up
the tablet, you will have to select the four points around the feature to
anchor the reference frame. For more information about Grid Pinning,
see “Using a Tablet to Collect Ground Control Points” on page 45.
The geocoded Easting and Northing coordinates transfer to the GCP
Collection window.
6. On the GCP Collection window under Georeferenced Position in
the Elev box, type the elevation of the GCP or you can use a digital
elevation model (DEM) to determine the elevation of your GCPs, see
“Using a Digital Elevation Model to Set Ground Control Point
Elevation” on page 51.
7. In the +/- boxes beside the Elev box, the Easting box, and the
Northing box, type the estimated error for each.
Tip
You can edit the error estimate in the +/- boxes under Image Position to
correspond to your ability to precisely identify a feature in the image. For
example, if you use coarse imagery, you can probably only measure to the
closest pixel. If you use imagery that was compressed or poorly scanned,
you may only be able to measure to the closest two pixels. Even if you
identify a GCP to the closest pixel, the coordinate may only be accurate to
so many meters.
Next step in your project . . .
For projects using the Aerial Photography or Satellite Orbital math models,
see “Collecting Tie Points Manually” on page 52. For other projects, see
“Understanding the Solution for Simple Math Models” on page 56.
Adding or Editing a Tablet
8. At a zoom level where you can see the detail in the raw image, position
the cursor precisely on the same feature that you selected on the paper
map and click Use Point.
The pixel and line coordinates from the raw image appear in the GCP
Collection window under Photo Position or Image Position.
9. Click Accept.
The GCP is added to the Accepted Points table.
OrthoEngine can work with any tablet that communicates using ASCII
characters. Most of the options used to configure the table can be found
in the tablet’s installation manual or user guide. A tablet configured in
ASCII mode reports actions and coordinates by sending a string of
characters to the computer. For OrthoEngine to interpret the strings of
characters, you must define the format that the tablet uses to create the
string. The format of the strings varies from tablet to tablet.
The tablet configurations are stored in tablet.def in the etc folder
where Geomatica is installed. For more information, see “Defining the
Tablet Format Strings” on page 60.
To add or modify a tablet:
In step 6 of “Setting Up the Tablet” on page 46:
1. In the Tablet type list, click Create to add a new tablet or click Edit
to modify the settings of an existing tablet.
Two windows open: Tablet Monitor and Tablet Configuration.
48
PCI Geomatics
Importing Ground Control Points from a File
2. On the Tablet Configuration window in the Tablet Name box,
type the name of the tablet that you are adding.
3. In the Device Name, type the communication port that you are using.
4. In the Baud Rate list, click the baud rate used by the tablet.
13. In the Format String, type the format of the command string used by
the tablet to communicate the coordinates. For more information, see
“Defining the Tablet Format Strings” on page 60.
14. When the tablet is communicating satisfactorily, click Configuration
Complete.
5. In the Parity list, click the parity bit setting used by the tablet.
6. In the Data Bits list, click the data bits used by the tablet.
7. In the Stop Bits list, click the stop bit used by the tablet.
8. In the Initialization box, type the command string that the tablet
sends to the computer to initiate communication.
9. In the Point Mode box, type the command string used by the tablet to
communicate how the coordinates are transmitted. In Point Mode a
coordinate is transmitted each time you click a button on the puck.
Importing Ground Control Points from a
File
If you have several raw images open, you will notice that one image
resides in a viewer labelled Working while the others are labelled
Reference. The GCP Collection window collects and displays the
GCPs from the image in the Working viewer only. Click Reference to
switch the viewer to Working. You can collect the same GCP in each
image by clicking Reference in a viewer, collecting the GCP, and then
repeating the process for each image.
10. In the Stream Mode box, type the command string used by the tablet
to communicate how the coordinates are transmitted. In Stream Mode
coordinates are transmitted continuously as you move the puck,
whether you click a button or not.
To import ground control points from a file:
11. In the Switch-stream Mode box, type the command string used by
the tablet to communicate how the coordinates are transmitted. In
Switch-stream Mode coordinates are transmitted continuously as you
drag the puck (press the button and move the puck).
2. Click
12. Click Connect to Tablet.
“Connect to Tablet” should appear in the Tablet Monitor window if
the tablet is communicating with the computer.
If you click the puck, a string appears in the Tablet Monitor. The
position where you clicked is reported as an ASCII string. The exact
format of this string varies between tablets. If the Format String is set
correctly, OrthoEngine will translate the string and “point read” will
follow the string.
OrthoEngine User’s Guide
1. On the OrthoEngine window in the Processing Step list, select
GCP Collection.
the Open new or existing photo icon to open an image.
For information how to open an image, see “Opening Images” on
page 17.
3. On the OrthoEngine window, click
File icon
the Import GCPs from
4. On the Read GCPs from Text File window, type the path for the
PCIDSK file containing the GCPs segment, the text file, or click Select
to select the file. The layout of the file is displayed under Example
Lines From GCP file.
5. If necessary, in the Format Description box type the string
representing the layout of the file or select a string from the Example
49
Chapter 5 - Collecting Control Points and Computing the Math Models
Formats list. Each character in the string represents a field in the text
file.
For example, the string IXYE represents the layout, where I is the
GCP’s identification, X and Y are the GCP’s geocoded x and y
coordinates, and E is the GCP’s elevation. For more information
about the strings in the Example Formats list, see “Understanding
Format Descriptions for Text Files Containing GCPs” on page 133.
6. Click Apply Format.
Successfully extracted GCPs appear under GCPs Extracted from
File. The GCPs are displayed as ID, pixel location, line location, x
coordinate, y coordinate, and elevation. Fields from the text file
without values appear as zero.
the GCPs are automatically added to the project and you can disregard
the following steps.
9. On the OrthoEngine window, click
Manually icon.
the Collect GCPs
10. On the GCP Text File window, click a GCP from the list and click
Transfer to GCP collection panel.
The GCP coordinates are transferred to the GCP Collection
window.
11. On the GCP Collection window in the +/- boxes beside the Elev
box, the Easting box, and the Northing box, type the estimated error
for each.
7. Click View/Edit to enter the projection of the GCPs being imported
from the file. To change the projection, type the projection string (for
example, UTM 17 T D000) in the text box beside the Earth Model
button.
If you do not know the projection string:
• Select a projection type the Coordinate System list.
(For UTM, State Plane Coordinate Systems (SPCS), or Other
projection types, additional windows may open automatically for
you to select the parameters to define the projection or click
More to open these windows. Select the parameters and click
Accept.)
12. At a zoom level where you can see the detail in the raw image, position
the cursor precisely on the feature that you will use as a GCP and then
click Use Point.
• Click Earth Model.
13. Click Accept.
• Click either the Datum or Ellipsoid tab.
The pixel and line coordinates from the raw image appear in the GCP
Collection window under Photo Position or Image Position.
The GCP is added to the Accepted Points table.
• Click a datum or an ellipsoid.
• Click Accept.
8. Click Accept.
If you did not import both the image coordinates and the ground
coordinates, the GCP Text File window opens. Continue with the
following steps. If you did import the image and ground coordinates,
50
Tip
You can edit the error estimate in the +/- boxes under Image Position to
correspond to your ability to precisely identify a feature in the image. For
example, if you use coarse imagery, you can probably only measure to the
closest pixel. If you use imagery that was compressed or poorly scanned,
you may only be able to measure to the closest two pixels. Even if you
PCI Geomatics
Using a Digital Elevation Model to Set Ground Control Point Elevation
identify a GCP to the closest pixel, the coordinate may only be accurate to
so many meters.
5. On the GCP Collection window under Georeferenced Position,
enter the Easting and Northing values by using one of the GCP
collection methods.
6. Under Auxiliary Information, click Extract Elevation.
Next step in your project . . .
For projects using the Aerial Photography or Satellite Orbital math models,
see “Collecting Tie Points Manually” on page 52. For other projects, see
“Understanding the Solution for Simple Math Models” on page 56.
Using a Digital Elevation Model to Set
Ground Control Point Elevation
If you chose the Aerial Photography, Satellite Orbital, Rational
Functions, or Thin Plate Spline math models, you can use a digital
elevation model (DEM) to determine the elevation of your ground
control points (GCPs). The DEM does not have to be in the same
projection as the source of the GCPs.
Understanding Tie Points
A tie point is a feature that you can clearly identify in two or more
images and that you can select as a reference point as shown in Figure
5.2. Tie points do not have known ground coordinates, but you can use
them to extend ground control over areas where you do not have
ground control points (GCPs). Used only in rigorous models such as
Aerial Photography and Satellite Orbital math models, tie points
identify how the images in your project relate to each other.
Figure 5.2: Example of how two images connect through a tie point
To use a DEM to set the GCP elevation:
1. On the GCP Collection window under Auxiliary Information,
click Select.
2. On the Database File Selection window, select the file and click
Open.
3. On DEM File window, select the database channel containing the
elevation.
4. In the Background Elevation box, type the value representing the
“No Data” pixels in the DEM and click Select.
If you do not know what the background value is, click DEM Info.
The DEM INFO window displays the three lowest and three highest
values. The background value is usually a dramatically different value
such as -150 or -999,999.
OrthoEngine User’s Guide
51
Chapter 5 - Collecting Control Points and Computing the Math Models
For projects using the Aerial Photography math model, you usually
collect tie points in a three-by-three pattern over the photograph as
shown in Figure 5.3. Since the photographs have a 60 percent overlap
between each other and a 20 percent overlap between the strips, you
can use the three-by-three pattern to connect six overlapping photos.
Figure 5.3: Six overlapping photographs showing the three-by-three pattern
• Choose features that you can identify accurately at the resolution of the
raw image.
• Select features that are close to the ground. Features that rise above the
ground, such as buildings, may appear to lean in the image. Therefore, a
point collected from the top of a feature in one image may be displaced
from the same point collected from the top of same feature in another
image.
• Avoid using shadows as tie points. Although shadows may be easy to
see in the image, they are not permanent and can move from one image
to another.
• Beware selecting common or repetitive features such as parking lots or
lines on a highway. When you try to identify the feature in the image, it
may be easy to select the wrong one.
• Select some tie points that appear in three or more images. Tie points
that join multiple images together produce a more accurate model.
Projects using the Satellite Orbital math model generally have fewer
images so you can collect tie points wherever overlap occurs. Since the
overlap between satellite images is unpredictable, satellite imagery
generally covers a large area containing a lot of ground control.
Using the tie points in the calculation of the math model ensures the
best fit not only for the individual images, but for all the images united
as a whole. Therefore, the images will fit the ground coordinate
system, and overlapping images will fit each other.
Note
See also “Choosing Quality Tie Points” on page 52.
Choosing Quality Tie Points
When you collect the tie points:
52
• If available, enter the elevation value of the tie point in the Tie Point
Collection window (see “Collecting Tie Points Manually” on page 52).
Tie points with an elevation value help to control elevation and improve
the accuracy of the geometric model.
Collecting Tie Points Manually
Used only in rigorous models such as Aerial Photography and Satellite
Orbital math models, tie points identify how the images in your project
relate to each other. For more information about tie points, see
“Understanding Tie Points” on page 51. You can also automate the tie
point collection process, see “Collecting Tie Points Automatically” on
page 53.
If you have several images open, you will notice that one image resides
in a viewer labelled Working while the others are labelled Reference.
The Tie Point Collection window collects and displays the tie points
from the image in the Working viewer only. Click the Reference
button to switch the viewer to Working. You can collect the same tie
point in each image by clicking Reference in a viewer, collecting the
tie point, and then repeating the process for each image.
PCI Geomatics
Collecting Tie Points Automatically
To collect tie points manually:
1. On the OrthoEngine window in the Processing Step list, select
GCP/TP Collection.
2. Click
the Open new or existing photo icon to open two or
more images.
For information how to open an image, see “Opening Images” on
page 17.
3. On the OrthoEngine window, click
points icon.
the Manually collect tie
4. On the GCP Collection window, the Point ID is generated
automatically. You can type a new label in the Point ID box, however,
all points (ground control points, check points, tie points, and elevation
match points) in the image must have unique labels.
5. You can select Auto Locate and/or Bundle Update to aid with
collection. For more information, see “Using Auto Locate” on page 35
and “Using Bundle Update” on page 36.
6. At a zoom level where you can see the detail in the raw image, position
the cursor precisely on the feature that you will use as a tie point and
then click Use Point.
You can open all the images that have the same feature in common
and collect the tie point for them all by selecting the feature in each
image and clicking Use Point in each image. The Tie Point
Collection window displays the tie points collected for the image
designated as Working.
7. You can also enter the tie point’s elevation (optional) by:
• On the Tie Point Collection window, select the Elevation
check box, type the elevation in the Elevation box, and type the
estimated error in the +/- box.
• Click Select and select a digital elevation model (DEM) that
covers the area. The elevation of the tie point is automatically
incorporated into the math model.
OrthoEngine User’s Guide
If you choose both of the above options, OrthoEngine will attempt to
find the elevation for each point in the DEM. If no elevation value is
available in the DEM, the value that you typed in the Elevation box
is used instead.
8. Under Reference Photo Tie Points, click Accept.
Tip
You can use the edges of lakes, parking lots, or flat fields as tie points with
elevation since it is easy to estimate the elevation of these points from
topographic maps or digital elevation models.
Next step in your project . . .
For the next step in your project, see “Performing the Bundle Adjustment for
Rigorous Math Models” on page 55.
Collecting Tie Points Automatically
Used only in rigorous models such as Aerial Photography and Satellite
Orbital math models, tie points identify how the images in your project
relate to each other. Since tie points are simply matching points in two
or more images, OrthoEngine can automate the tie point collection by
using image correlation techniques.
To collect tie points automatically:
1. On the OrthoEngine window in the Processing Step list, select
GCP/TP Collection.
2. On the OrthoEngine window, click
collect tie points icon.
the Automatically
3. On the Automatic Tie Point Collection window in the No. of Tie
Points per Area box, type the number of tie points that you will use
over the image or overlap area.
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Chapter 5 - Collecting Control Points and Computing the Math Models
4. In the Matching Threshold box, type a value between zero and one.
The Matching Threshold is the minimum correlation score that will
be considered a successful match. The best correlation score is one.
5. In the Approx. Elevation box, type the approximate elevation of the
terrain.
6. You can also use a DEM to determine the elevation of the tie point.
Under Auxiliary Information, click Select and select a digital
elevation model (DEM) that covers the area. The elevations of the tie
points are automatically incorporated into the math model. However,
using a DEM increases the processing time since it causes iterative
computation of the model.
If you choose both of the above options, OrthoEngine will attempt to
find the elevation for each point in the DEM. If no elevation value is
available in the DEM, the value that you typed in the Approx.
Elevation box is used instead.
7. Under Photos to Process (or Images to Process), click All Photos
(or All Images) to collect tie points for all the images in the project or
click Working Photo (Working Images) to collect tie points for the
photograph or image designated as Working.
8. Under Tie Point Distribution Pattern, click:
• Uniformly over area of each Photo (or Image) to distribute
the tie points evenly over the entire image and match each tie
point in all the overlapping images. This is normally used to
generate standard tie point distributions for aerial photographs
such as the three-by-three pattern.
• Per Overlapping Area to distribute the points evenly only in the
overlap area between any pair of overlapping images. This is
normally used for satellite images or for aerial photographs with
less than 60% overlap.
10. Click Start Auto Tie Point Matching.
11. Click Close.
Next step in your project . . .
For the next step in your project, see “Performing the Bundle Adjustment for
Rigorous Math Models” on page 55.
Displaying the Overall Layout
The Overall Layout feature is a quality control tool that reveals the
relative positioning of the image footprints and displays a plot of the
distribution of the ground control points (GCPs) and tie points for the
entire project. Images in the project are represented by a frame with
crosshairs and ID at the center. If information is insufficient to position
the images relative to the ground, a message will appear in the status
bar to indicate that you need to collect more GCPs.
Table 2: Symbols
Item
Symbol
Selected image
red frame
Reference image
dark blue frame
Offline image
black frame
Other image
light blue frame
GCP
small red square
GCP existing on more than one image
large dark red square
Tie point
blue square
Tie point existing on more than one image
large dark blue square
9. Under Processing Start Time, click Start Now or Start at
(hh:mm) and set the time when you want the operation to begin
(within the next 24 hours).
54
PCI Geomatics
Understanding the Bundle Adjustment for Rigorous Math Models
To display the overall layout:
1. On the OrthoEngine window in the Processing Step list, select
GCP Collection.
2. On the OrthoEngine window, click
image layout icon.
the Display overall
3. Under Overview, click a crosshair to reveal the image’s footprint. To
open the image, double-click the image footprint. The top of the
window points northward.
If you are not satisfied with the distribution, edit your GCPs and tie
points.
Understanding the Bundle Adjustment for
Rigorous Math Models
The bundle adjustment is simply the computation of a rigorous math
model. It is a method to calculate the position and orientation of the
sensor—the aerial camera or satellite—at the time when the image was
taken. Once the position and orientation of the sensor is identified, it
can be used to accurately account for known distortions in the image.
In the Aerial Photography math model, the geometry of the camera is
described by six independent parameters, called the elements of
exterior orientation. The three-dimensional coordinates x, y, and z of
the exposure station in a ground coordinate system identify the space
position of the aerial camera. The z-coordinate is the flying height
above the datum, not above the ground. The angular orientation of the
camera is described by three rotation angles: Omega, Phi, and Kappa.
For more information on exterior orientation, see “Understanding
Exterior Orientation” on page 26.
In the Satellite Orbital math model, the position and orientation of the
satellite is described by a combination of several variables of the
viewing geometry reflecting the effects due to the platform position,
velocity, sensor orientation, integration time, and field of view.
OrthoEngine User’s Guide
The bundle adjustment uses ground control points (GCPs) and tie
points combined with the knowledge of the rigorous geometry of the
sensor to calculate the best fit for all images in the project
simultaneously.
For Aerial Photography projects, the bundle adjustment can only be
computed after you collect the minimum number of ground control
points (GCPs) and tie points. If you are using data from the Global
Positioning System (GPS) with or without Inertial Navigation System
(INS) data, the bundle adjustment can be computed immediately. Due
to the ephemeris data, the bundle adjustment for Satellite Orbital
projects is computed immediately with or without GCPs or tie points.
You can add GCPs and tie points to refine the math model’s solution.
Not all the GCPs in your project will have the same reliability. When
the bundle adjustment is computed, the GCPs, tie points, GPS data, and
INS data will be automatically weighted inversely to their estimated
error. The most accurate GCPs or tie points should affect the solution
the most, and the least reliable should affect the solution the least.
Using many GCPs and tie points provides redundancy in the
observations so that a few bad points will not greatly affect your model,
and the bad points will be easier to identify.
Once the sensor orientation is calculated, it is used to drive all the other
processes such as digital elevation model extraction, editing in threedimensional stereo, and orthorectification. You must obtain an
accurate bundle adjustment solution before continuing with other
processes.
Performing the Bundle Adjustment for
Rigorous Math Models
The bundle adjustment is the computation of the rigorous math model.
The image is not manipulated at this point. For more information, see
“Understanding the Bundle Adjustment for Rigorous Math Models” on
page 55.
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Chapter 5 - Collecting Control Points and Computing the Math Models
To compute the rigorous math model:
1. On the OrthoEngine window in the Processing Step list, select
Model Calculations.
2. On the OrthoEngine window, click
Adjustment icon.
the Perform Bundle
Next step in your project . . .
For the next step in your project, see “Troubleshooting the Math Model
Solution” on page 56.
Understanding the Solution for Simple
Math Models
The computation of the simple models is done automatically as you add
ground control points (GCPs) to the project. The image is not
manipulated at this point. The simple math model uses the GCPs to
calculate a transformation that will warp the raw image to fit the
ground coordinates. Since the math model calculates a solution for
each image, no tie points are used.
Rational Functions: The rational functions math model solution uses
the GCPs to build a relationship between the pixels and the ground
locations. To evaluate the accuracy of your model, see
“Troubleshooting the Math Model Solution” on page 56.
Next step in your project . . .
For Rational Functions projects, see “Understanding Digital Elevation
Models” on page 63, “Understanding 3-D Stereo Viewing and Editing” on
page 81, or “Geometrically Correcting Your Images” on page 101.
Polynomial: The Polynomial math model’s solution is used to warp
the raw image around the GCPs to fit the ground coordinate system. To
56
evaluate the accuracy of your model, see “Troubleshooting the Math
Model Solution” on page 56.
Next step in your project . . .
For Polynomial projects, see “Geometrically Correcting Your Images” on
page 101.
Thin Plate Spline: The Thin Plate Spline math model solution will use
the GCPs simultaneously to fit the raw image to the ground coordinate
system by distributing the transformation over the entire image. To
evaluate the accuracy of your model, see “Troubleshooting the Math
Model Solution” on page 56.
Next step in your project . . .
For Thin Plate Spline projects, see “Generating Digital Elevation Models” on
page 63 or “Correcting Your Images” on page 97
Troubleshooting the Math Model Solution
Since determining the best possible solution for the math model is the
foundation of your project, it is important for you to know if your
solution is good enough to achieve the results you expect. If it is not,
you must also know what to do to adjust the model.
The Residual Errors will help you determine if the solution is good
enough for your project. Residual errors are the difference between the
coordinates that you entered for the ground control points (GCPs) or
tie points and where those points are according to the computed math
model. You can see the residual errors for the image on the GCP
Collection windows in the Residual column or you can generate a
Residual Report for the entire project (see “Generating a Residual
Report” on page 58).
PCI Geomatics
Troubleshooting the Math Model Solution
Residual errors do not necessarily reflect errors in the GCPs or tie
points, but rather the overall quality of the math model. In other words,
residual errors are not necessarily mistakes that need to be
corrected. They may indicate bad points, but, generally, they simply
indicate how well the computed math model fits the ground control
system.
Note
In Rational Functions, Polynomial, and Thin Plate Spline projects, images
are not connected together with tie points. Therefore, the math model and
the resulting residual errors are calculated for each image separately. If you
selected the Thin Plate Spline math model for your project, the residual
errors will always indicate zero. Use Check Points to check its accuracy.
Another way to verify the quality of the model is to collect some GCPs
as Check Points. Check points are not used to compute the math model,
but OrthoEngine calculates the difference between their position and
the position determined by the model and includes the error in the
Residual Errors report. Therefore, the Check Points provide an
independent accuracy assessment of the math model.
In most projects you should aim for the residual errors to be one pixel
or less. However, you should also consider how the resolution of the
image, the accuracy of your ground control source, and the
compatibility between your ground control source and the images can
affect the residual errors.
• You may want to use a topographic map as a ground control source,
however, features on topographic maps may be shifted several meters
for aesthetic reasons. This limits the accuracy of the coordinates that
you can obtain from the map. Also, the detail visible on a 1:50,000
scale topographic map may not be compatible with the high resolution
of an aerial photograph. For example, if you choose a road intersection
in a topographic map as your coordinate, the same road intersection in
the aerial photograph may consist of several pixels. Therefore, the
residual error will likely be larger than a pixel.
OrthoEngine User’s Guide
• An existing LANDSAT orthorectified image may make a convenient
ground control source for registering a new IKONOS image, but the
resolution of the LANDSAT image is 30 meters and the resolution of
the IKONOS raw image is 1 meter. Therefore, even if you could pick
the right pixel in the IKONOS image, your GCP from the LANDSAT
image is only accurate to 30 meters. You cannot achieve accuracy of 2
to 4 meters unless your ground control source is equally accurate.
• At first glance, a residual error of 250 meters in ground distance may
appear too high. However, if your raw data has a resolution of 1000
meters, such as AVHRR, you have already achieved sub-pixel accuracy.
Identifying Errors in the Math Model
Although residual errors are not necessarily mistakes that need to be
corrected, they may indicate problems with the math model. The
following conditions may help you to identify such problems.
One or More GCPs or Tie Points with Very High Residual Errors
A ground control point (GCP) or tie point with a very high residual
error compared to the others in the Residual Errors report may indicate
an error in the original GCP coordinate, a typographical mistake, or an
error in the position of the GCP or tie point on the raw image. These
points are called outliers.
To correct an outlier:
• Verify that the feature that you picked in the raw image corresponds to
the one from your source.
• Verify that the typed ground coordinate matches the coordinate listed in
your source.
• Confirm that the ground coordinate that you collected in the raw image
is consistent with the coordinate that you selected from the vector or the
geocoded image.
• Verify that the projection and datum for the ground coordinate are
correct.
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Chapter 5 - Collecting Control Points and Computing the Math Models
If all else fails, delete the point or change it to a Check Point. For
information about Check Points, see “Troubleshooting the Math Model
Solution” on page 56.
Overall High Residual Errors
If the residual errors for all the GCPs and/or tie points in general are
high, it may indicate a poor model solution. Poor model solutions can
be the result of inaccurate GCPs, errors in the projection or datum,
inadequate distribution of the ground control, or insufficient ground
control.
Residual Errors Are All Zero
If all the residual errors for the GCPs and tie points read zero, it usually
indicates that you have collected only the minimum number of ground
control points or fewer. Collect more GCPs and tie points.
However, if you selected the Thin Plate Spline math model for your
project, the residual errors will always indicate zero. Use Check Points
to check the accuracy for the Thin Plate Spline math model. For more
information on Thin Plate Spline, see “Understanding the Thin Plate
Spline Math Model” on page 8. For more information on Check Points,
“Troubleshooting the Math Model Solution” on page 56.
Systematic Trends in Residual Errors
If you have high residual errors in one part of an image or project, it
can indicate that you need more ground control in the problem area, or
it may indicate that you have one or more bad points in the area that are
skewing the math model. Some bad points are difficult to identify since
some points may compensate for others.
“Editing Features in 3-D Stereo” on page 81
“Correcting Your Images” on page 97
Generating a Residual Report
The Residual Report helps you determine if the math model solution is
good enough for your project. Residual errors do not necessarily reflect
errors in the GCPs or tie points, but rather the overall quality of the
math model. In other words, residual errors are not necessarily
mistakes that need to be corrected. They may indicate bad points,
but, generally, they simply indicate how well the computed math
model fits the ground control system. For more information, see
“Troubleshooting the Math Model Solution” on page 56.
Note
Depending on the math model that you chose, the features available may
vary.
To generate a Residual Report:
1. On the OrthoEngine window in the Processing Step list, select
Reports.
2. Click
the Residual report icon.
3. Under Residual Units, click the measurement unit that you want
displayed in the report.
4. Under Show Points, click:
• All to display all the points collected.
• GCPs/Check Pts to display only the ground control points and
the check points.
Next step in your project . . .
For the next step in your project, see one of the following
“Generating Digital Elevation Models” on page 63
58
• Tie Points to display only the tie points.
• Stereo GCPs to display the points that appear on more than one
image.
PCI Geomatics
Editing Points in the Residual Report
5. Under Show in, click:
• All Photos to display all the images in the project.
• Click an image in the table under Photo ID or type the image’s
identification in the Selected Photo ID box. Click Selected
Photo to display one image in the project.
6. Under Sort by, click:
• Residual to order the residual errors from the highest to the
lowest value.
• Data Snooping to order the normalized residual errors from
highest to lowest probability of error that is not noise. This feature
is available after the bundle adjustment is performed.
7. Edit the points as required. For more information, see “Editing Points
in the Residual Report” on page 59.
8. Click:
• Print to File to save the report in a text file. In Report File, type
the path for the text file or click Select to choose a location. Click
Append to the report to an existing file or click Overwrite to
replace or create a file.
• Perform Bundle Adjustment to compute the solution for the
rigorous math model. For more information, see “Understanding
the Bundle Adjustment for Rigorous Math Models” on page 55.
Next step in your project . . .
See “Editing Points in the Residual Report” on page 59.
understand how to evaluate the points in your project, see
“Troubleshooting the Math Model Solution” on page 56.
To edit the points in your project:
1. In the table on the Residual Errors window, click the image that
contains the point that you want to edit. Click Edit Point.
2. The viewer and GCP Collection or Tie Point Collection window
open for the selected point. In the viewer click to indicate the new
location of the point and click Use Point.
3. Click Accept.
4. Verify the results in the table. If you are not satisfied, select the same
point in the table on the Residual Errors window, click Edit Point,
and repeat the process.
5. If you decide that the point is still not acceptable, click:
• Delete Point to remove the point from the project.
• Change to Check Point to remove the point from the math
model calculations, but keep the point in the project.
OrthoEngine calculates the difference between the Check
Point’s position and the position determined by the model and
includes the error in the Residual Report. Therefore, the Check
Points provide an independent accuracy assessment of the
math model.
Note
Press SHIFT and click to select a range of neighboring points or press
CTRL and click separate points.
Editing Points in the Residual Report
The Residual Report contains the residual errors for the points in your
project. Residual errors are the difference between the coordinates that
you entered for the ground control points (GCPs) or tie points and
where the points are according to the computed math model. To
OrthoEngine User’s Guide
Next step in your project . . .
See “Understanding Digital Elevation Models” on page 63, “Understanding
3-D Stereo Viewing and Editing” on page 81, or “Orthorectifying Your
Images” on page 98.
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Chapter 5 - Collecting Control Points and Computing the Math Models
Defining the Tablet Format Strings
Tablets are usually attached to RS-232C ports (terminal ports). Like
other RS-232C devices, you must configure the connection between
the tablet and the port correctly. Most tablets come with jumpers or
toggle switches that provide a range of possible baud rates, parity, data
bit size, and stop bits.
Check the documentation for the tablet to find which characteristics
can be changed, and how to interpret the current settings. In most cases
you can use the default settings with OrthoEngine. Configuring the
communication depends on the operating system and the tablet used.
For most systems, you must:
1. Disable the logins on the port where the tablet is connected.
M: Part of button number, first button is number 0
N: Part of button number, first button is number 1
H: Hex button number (0-E)
X: Part of X location
Y: Part of Y location
S: The sign (“+” or “-”) of the following number
B: Generic place holder
Any character not in this list is used for verification when converting
raw data into points. You can use a maximum of two button characters
unless the button number is hexadecimal. When the button number is
hexadecimal, you can use only one button number. You must use either
M, N, or H to indicate the button pressed.
For example, the SummaGraphics Microgrid generates an ASCII string
in the following format:
2. Set the port to match the baud, parity, data bits and stop bits of the
tablet.
SXXXXX,SYYYYY,NN,T
Commands are sent to the tablet for initialization and changing modes.
The command string consists of a series of characters and special
functions. Regular text spaces are ignored in the command string,
which provides some flexibility in creating a legible command string.
The functions available are:
where,
\PAUSE(n):Pause for n seconds, where n is real.
(For example, \PAUSE(1.2) will pause for 1.2 seconds.)
\ASCII(n):Send the ASCII character corresponding to the decimal
number n.
\SPACE:Insert a space character.
\SLASH:Insert a back-slash character (\).
\CR:Insert a carriage return equivalent to \ASCII(13)
\LF:Insert a line feed equivalent to \ASCII(10).
\ESC:Insert an escape character equivalent to \ASCII(27).
If the tablet is not supported by PCI Geomatics, you must define the
format string. A format string is defined using the following
characters:
60
S is the sign (“+” or “-”) of the number,
XXXXX are five digits giving the x location,
YYYYY are five digits giving the y location,
NN is the number of the button pressed, in this case a number between
0 and 16,
T is a tablet area identifier.
Format string rules:
1. A sign character, if present, must occur immediately before the XXX or
YYY characters otherwise it will be ignored.
2. Only the first occurrence of XXX, YYY, and NN in the format string
are used (others are ignored).
The tablet configurations are stored in a text file $PCIHOME/etc/
tablet.def. that contains a number of parameters which define a tablet.
Each parameter must appear on a separate line. A tablet is defined by
the following parameters:
PCI Geomatics
Defining the Tablet Format Strings
TABLET(tablet number)
NAME(tablet name)
INITIALIZE(init string)
FORMAT(format string)
STREAM(stream mode)
POINT(point mode)
SWITCH(switch stream mode)
BAUD(baud rate)
PARITY(parity)
DATA(data bits)
STOP(stop bits)
Only the TABLET, NAME, and FORMAT parameters are required.
Omit any parameters that you do not know.
Each new tablet definition begins with the TABLET(tablet number)
command, where n specifies a unique tablet number. Tablet numbers
below 10 are reserved for PCI definitions. The parameters may be
separated by comment lines. A comment is indicated by placing a
number sign (#) character at the beginning of the line.
All other parameters may appear in any order following the TABLET
parameter. The init string, point mode, switch stream mode, and stream
mode parameters must be valid command strings. The tablet name
parameter is the name of the tablet as it would appear in an option
menu.
OrthoEngine User’s Guide
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Chapter 5 - Collecting Control Points and Computing the Math Models
62
PCI Geomatics
CHAPTER
6
Generating Digital Elevation Models
Understanding Digital Elevation Models
A digital elevation model (DEM) is a digital file of terrain elevations
for ground positions. It is a raster representing the elevation of the
ground and objects, such as buildings and trees, with pixel values in the
images.
In most cases, the best source of elevation for your project is a good
DEM. You may want to use a DEM when you are orthorectifying an
image to provide geometric correction for relief displacement, or when
you do not have surveyed elevation measurements for your ground
control points (GCPs) and/or tie points.
You should make sure that the DEM will provide the level of accuracy
that you require for your project, and that it includes the features that
you are trying to analyse. For example,
• When you want an orthorectified image that is accurate to 0.01 meters,
a DEM with 1 kilometer resolution will probably not deliver the
accuracy you need.
• If you want to analyse highway overpasses, a DEM that was smoothed
and resampled to 30 meters will not provide the details that you need.
• If you want a smooth, low resolution orthorectified image, a DEM
containing fine features, such as buildings, may contain too much
detail.
Besides providing a source of elevation, the DEM itself has many uses.
For example:
• Geologists use DEMs to identify geological structures in topography.
• Mapping agencies use DEMs as the source of topographic information
and contour lines for maps.
• Environmentalists use DEMs to identify risk areas and flow patterns.
• Disaster management agencies use DEMs to identify flood risk areas
and to determine accessibility.
• Telecommunications companies use DEMs to identify regions of
visibility for radio or cell towers. They can also use the texture of the
DEM to predict how the terrain can effect signal strength and reflection.
Next step in your project . . .
See one of the following:
“Using Rasters to Generate a Digital Elevation Model” on page 64
“Using Ground Control Points, Tie Points, and/or Elevation Match Points to
63
Chapter 6 - Generating Digital Elevation Models
Generate a Digital Elevation Model” on page 64
“Using Vectors to Generate a Digital Elevation Model” on page 65
“Extracting Digital Elevation Models from Epipolar Pairs” on page 71
4. Click Move Up and Move Down as required to organize the files
under Set of DEMs to Merge. When a raster from the bottom of the
list overlaps a raster from the top of the list, the bottom raster will
overwrite the top raster where the two overlap.
Using Rasters to Generate a Digital
Elevation Model
5. In the Channel list, click the channel that you want to use or click
Select.
Data providers and government agencies offer digital elevation models
(DEMs) as rasters. Many raster DEMs are available without charge and
can be downloaded from the Web. For example, the USGS distributes
its DEM products, which are based on USGS Digital Orthophoto
Quads and Quarter Quads (DOQs, DOQQs), from their Web site.
6. In the Background Value box, type the value representing the “No
Data” pixels in the DEM.
Since you may not find one raster DEM that meets your requirements,
you can merge several existing DEM raster files to generate a single
seamless DEM to cover your project area.
8. In Interpolate Holes, you can click Yes to automatically interpolate
data between the raster DEMs. This is recommended for small gaps,
but not for large areas.
Also, if you generated your own DEMs and chose to edit them before
they were geocoded (see “Extracting Digital Elevation Models from
Epipolar Pairs” on page 71), you can integrate the resulting geocoded
DEMs with this procedure.
9. Click Accept.
To import raster files to generate a DEM:
1. On the OrthoEngine window in the Processing Step list, select
Import & Build DEM.
2. Click
the DEM from raster file icon.
3. On the Input DEM File Selection window, type the path of a raster
file or click Select to select a file.
To select more than one file: On the Input DEM File Selection
window in the File(s) box, type the path with a wildcard character in
the filename and press ENTER. For example,
C:\Geomatica\demo\*.pix.Under DEM Merge Set Candidates,
click the files of your choice and click the arrow.
64
7. In the Resampling list, click the processing method of your choice.
For more information, see “Understanding the Resampling Options” on
page 104.
Next step in your project . . .
See “Generating the Digital Elevation Model from Rasters, Vectors, or
Control Points” on page 67.
Using Ground Control Points, Tie Points,
and/or Elevation Match Points to
Generate a Digital Elevation Model
OrthoEngine uses the math model solution (known exterior
orientation) and the pixel and line positions of the points in common in
the overlapping images to generate a digital elevation model (DEM).
The elevations are calculated from the parallax between the
corresponding ground control points (GCPs), tie points, and elevation
match points in the images.
PCI Geomatics
Using Vectors to Generate a Digital Elevation Model
The DEM can be fairly accurate for relatively flat areas, however, it is
not recommended for rough areas since you would have to collect a
large number of points to accurately represent the terrain.
To collect elevation match points:
1. On the OrthoEngine window in the Processing Step list, select
Import & Build DEM.
2. Click
the DEM from GCPs/Tie points/Match points icon.
3. On the Elevation Match Point Collection window, the Point ID is
generated automatically. You can type a new label in the Point ID
box, however, all points (ground control points, check points, tie
points, and elevation match points) in the image must have unique
labels.
4. You can select Auto Locate to aid with collection. For more
information, see “Using Auto Locate” on page 35.
5. In the Photo Layout window under Overview, double-click the
crosshairs of two overlapping images.
6. Choose a feature that appears in both images. At a zoom level where
you can see the detail in one of the images, position the cursor precisely
on the feature and then click Use Point. At a zoom level where you
can see the detail in the second image, position the cursor precisely on
the same feature and then click Use Point.
The pixel and line coordinates from the feature in each image appear
in the Elevation Match Point Collection window under Photo
Positions.
7. In the Elevation Match Point Collection window, click Accept.
The point and its elevation appear under Accepted Elevation Match
Points. Collect as many points as needed to satisfactorily express the
terrain.
OrthoEngine User’s Guide
8. To edit a point, click the point under Accepted Elevation Match
Points. Under Photo Positions, click Quick Open beside the image
that you want to edit. Reposition the cursor precisely on the feature,
click Use Point, and then click Accept.
To remove a point, click the point under Accepted Elevation Match
Points and click Delete.
9. Click:
• Create DEM to generate a DEM from the points. When Include
GCP _Tie Points to Build DEM? appears, click Yes if you
want to use the project’s ground control points and tie points to
generate the DEM.
• Add to DEM to add the points to an existing DEM. This is useful
if you want to add more points to an area where you are not
satisfied with the results.
• Save Pts to File to save the points to an ASCII file. Type the
path for the file that you want to add the points to or click Browse
to select a file. Click Create. If the text file exists, you can click
Append to add the points to the end of the file or click Delete to
remove the file and create a new one.
10. Click Close.
Next step in your project . . .
See “Generating the Digital Elevation Model from Rasters, Vectors, or
Control Points” on page 67.
Using Vectors to Generate a Digital
Elevation Model
OrthoEngine can calculate the elevations from vector layers to
generate a raster digital elevation model (DEM). OrthoEngine uses
raster DEMs to orthorectify images. If your elevation data is stored as
vectors such as contours, points, TIN, or even a text file containing
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Chapter 6 - Generating Digital Elevation Models
coordinates, you can convert them into a raster DEM as long as the
vectors are in any of the supported formats.
The vector layers from the file appear under Input File Vector
Layers.
Note
You can combine vectors from different layers and files to generate a DEM.
Vector layers can contain:
• Points: A point is a single coordinate (x, y, and z).
• Lines: A line is a start and end coordinate with points in between to
define the shape.
• Polygons: A polygon is a line with the same start and end coordinate
forming an area with numerous points along the line to define its size
and shape.
• Contours: A contour is a line formed by a set of points representing
the same value of a selected attribute. Contours are usually used to
represent connecting points on the ground with the same elevation.
• TIN: A Triangulated Irregular Network (TIN) is a digital model of
adjoining triangles formed from points selected on the terrain to
represent an accurate model of the surface. The TIN model can contain
coordinates and other geographical data.
To import vector files to generate a DEM:
1. On the OrthoEngine window in the Processing Step list, select
Import & Build DEM.
2. Click one of the following:
DEM from vectors/points
DEM from contours
DEM from TIN
66
3. On the Input Vector Layer Selection window in the Vector File
box, type the path of a vector file or click Select to select a file.
4. Under Input File Vector Layers, click the layers of your choice and
click the arrow.
The selected layers that will form the DEM appear under Set of
Vector Layers to Interpolate.
5. To add vectors from other files, repeat steps 3 and 4.
6. In the Data Type list, select the type of vector in the layer. Click:
• Points for a layer containing only points or one vertex.
• Contours for a layer of vector lines with elevation values.
• 3D Lines for a layer with three-dimensional (3-D) breaklines or
features.
• Valleys (2D) for a layer of two-dimensional (2-D) breaklines
without elevation values that is used to represent valleys.
• Ridges (2D) for a layer of 2-D breaklines without elevation
values that is used to represent ridges.
• Cliffs (2D) for a layer of 2-D breaklines representing cliffs,
which are treated as a local discontinuity. The interpolated
elevations from either side of the breaklines may be radically
different.
• TIN for a layer of 3-D breaklines using the TIN model.
The 2-D layers provide additional constraints for the interpolation of
the source elevations. In particular, a valley vector indicates a local
minimum, a ridge vector indicates a local maximum, and a cliff
vector indicates a discontinuity in the DEM.
7. In the Elevation Source list, click where the elevation value is stored.
The elevation values can be stored in several ways such as the z
coordinate of the feature or in an attribute field.
PCI Geomatics
Generating the Digital Elevation Model from Rasters, Vectors, or Control Points
8. Click Accept.
Next step in your project . . .
See “Generating the Digital Elevation Model from Rasters, Vectors, or
Control Points” on page 67.
Generating the Digital Elevation Model
from Rasters, Vectors, or Control Points
Import the source for generating the DEM with one of the following:
• “Using Rasters to Generate a Digital Elevation Model” on
page 64
• “Using Ground Control Points, Tie Points, and/or Elevation
Match Points to Generate a Digital Elevation Model” on page 64
• “Using Vectors to Generate a Digital Elevation Model” on
page 65.
After importing the source for generating the digital elevation model
(DEM), you determine the parameters of the DEM output.
To determine the output parameters:
1. On the Define Output DEM file window in the Output DEM box,
type the path where you want to save the DEM or click Select to
determine the path.
2. Click one of the following:
• Mosaic Area to generate a DEM that covers the area defined by
the Mosaic Area.
• Elevation Source Area to generate a DEM that covers the area
where elevation data exists (recommended).
• Photo Extents to generate a DEM that covers the extents of all
the photos in the project. This is useful when you want the DEM
to cover the images being orthorectified, but extrapolating beyond
OrthoEngine User’s Guide
the elevation source area can cause significant errors in your
project.
3. In the Background Elevation box, type the value to represent the
background or “No Data” pixels in the DEM.
4. Three parameters determine the final output of the DEM: the size, the
resolution, and the bounds of the DEM. You can specify two out of the
three, and OrthoEngine with calculate the third:
• To set the size and bounds for the DEM, click Use pixels/lines
and bounds in the list.
• To set the size and resolution for the DEM, click Use pixels/lines
and resolution in the list.
• To set the bounds and resolution for the DEM, click Use bounds
and resolution in the list.
5. Depending on which option you selected in step 4, set the two
parameters of your choice:
• To set the Size: Type the number of pixels in the Pixel box and
type the number of lines in the Lines box to determine the size of
the DEM.
• To set the Resolution: Type the x and y dimensions of the pixel
size in the corresponding X and Y boxes.
• To set the Bounds: In the Bounds list, click Geocoded to enter
the bounds in georeferenced units or click Geographic to use
Longitude/Latitude units. In the Upper Left boxes, type the
coordinates of the upper-left corner of the DEM. In the Lower
Right boxes, type the coordinates of the lower-right corner of the
DEM.
6. Click Generate DEM.
7. If you are generating a DEM from vectors, you must select an
interpolation method. For more information about the methods, see
“Understanding the Interpolation Methods for Vectors” on page 68.
Select:
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Chapter 6 - Generating Digital Elevation Models
• Natural Neighbor Interpolation to use the Natural Neighbor
algorithm to interpolate the DEM from points. It is recommended
for files that contain sparsely distributed or unevenly distributed
points since it performs a more intelligent calculation than Finite
Difference. However, it is not recommended for files that contain
a large number of points since the calculations required will take
considerable more time to process.
• Finite Difference to use the Distance Transform and Finite
Difference algorithms to interpolate the DEM from points. It is
recommended for files that contain evenly distributed points. It
can rapidly process an unlimited number of points.
• In the No of Iteration list, type the maximum number of times
that the DEM is smoothed.
• In the Tolerance box, type the minimum difference in value
required during smoothing to warrant another application.
8. If the DEM is satisfactory, click Accept DEM.
Understanding the Interpolation Methods for Vectors
When you generate a digital elevation model (DEM) from vector, you
must determine how the values between the vectors and the raster are
calculated.
Natural Neighbor Interpolation
This method is only available when you are generating a DEM from
points. The Natural Neighbours algorithm constructs circles using
three points based on the Delaunay triangle. OrthoEngine calculates
the pixel values by using all the points to form the least number of the
largest possible circles. Inside each circle the interpolated values are
influenced by the three points forming the Delaunay triangle and all the
circles that overlap that circle.
calculations required will take considerable more time to process.
Since it does not extrapolate beyond the bounds of the points, it may
also leave areas of the interpolated DEM empty.
Finite Difference
This method performs the interpolation in three steps. In the first step,
the vector elevation values are encoded into the corresponding pixels
in the raster DEM. In the second step, the elevations for the remaining
pixels are interpolated using the Distance Transform algorithm, which
estimates the values from pixels equidistant from the pixels encoded in
the first step. In the third step, the Finite Difference algorithm
iteratively smooths the raster DEM. During the iterations, the pixels
that were encoded in the first step are not changed, while the
interpolated pixel values are updated based on the neighbourhood
values.
Two parameters determine the completion of the process, No. of
Iterations and Tolerance. The No. of Iterations parameter specifies
the maximum number of times smoothing is applied to the raster DEM.
The default is 10. Tolerance restricts the number of times smoothing is
applied according to how it changes the elevation values of the pixels.
The default is 1.
For example, you set the No. of Iterations to 10 and the Tolerance to 1
meter. Smoothing can be applied up to 10 times, but smoothing ceases
as soon as the smoothing causes a change of less than 1 meter in the
elevation values. If the maximum change on the third iteration is only
0.3 meters, then only three iterations of the smoothing are applied.
Finite Difference is recommended for files that contain evenly
distributed points. Since it is a simpler technique, it processes the raster
DEM much faster, and it is better suited to large input data sets.
Natural Neighbor Interpolation is recommended for files that contain
sparsely distributed or unevenly distributed points since it performs a
more intelligent calculation than Finite Difference. However, it is not
recommended for files that contain a large number of points since the
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PCI Geomatics
Building a Digital Elevation Model from a Stereo Pair of Images
Building a Digital Elevation Model from a
Stereo Pair of Images
You can create a digital elevation model (DEM) from stereo pairs of
images, which are two or more images of the same area taken from
different view points. This method can be very useful for creating a
DEM for inaccessible areas. You can obtain stereo pairs from aerial
photographs, digital or video images, and these sensors: ASAR,
ASTER, IRS, IKONOS, SPOT, QUICKBIRD, and RADARSAT.
Tip
To help you select a RADARSAT stereo pair, CCRS provides an interactive
Web tool. See http://www.pcigeomatics.com/support/FAQ/oe_data.htm.
Next step in your project . . .
See “Creating Epipolar Images” on page 69.
Creating Epipolar Images
Epipolar images are stereo pairs that are reprojected so that the left and
right images have a common orientation, and matching features
between the images appear along a common x axis. Using epipolar
images increases the speed of the correlation process and reduces the
possibility of incorrect matches.
Figure 6.2: Comparing raw images to epipolar images
OrthoEngine uses image correlation to extract matching pixels in the
two images and then uses the sensor geometry from the computed math
model to calculate x, y, and z positions.
Figure 6.1: Creating a DEM from stereo pairs
To create epipolar images:
1. On the OrthoEngine window in the Processing Step list, select
DEM From Stereo.
2. Click
the Create Epipolar Image icon.
3. In the list under Epipolar Selection, choose one of the following
options. Click:
• User Select to select the pairs manually. Under Left Image and
Right Image, click the images that you want to form the pair. For
ASTER images, use the nadir image as your left image. For
OrthoEngine User’s Guide
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Chapter 6 - Generating Digital Elevation Models
RADARSAT images, use the image with the larger incidence
angle as your left image.
• Maximum Overlapping Pairs to automatically select the pairs
that demonstrate the highest amount of overlap. Each image
forms pairs with the two images that overlap it the most. In the
Minimum Percentage Overlap box, type or select the lowest
percent of overlap acceptable between two images to be
considered a valid pair.
• All Overlapping Pairs to automatically select all the pairs that
overlap above the specified minimum percentage. In the
Minimum Percentage Overlap box, type or select the lowest
percent of overlap acceptable between two images to be
considered a valid pair.
Figure 6.3: Comparing All Overlapping Pairs and Maximum Overlapping Pairs
• To select or remove a pair from the list, under the Select column
click to select or clear the check mark of the pair of your choice.
To select all the pairs in the list, click Select All. To clear all the
check marks, click Select None.
• To eliminate one pair from the list, under the Number column
click the pair of your choice and click Remove. To eliminate all
the pairs from the list, click Remove All.
• To interchange the left and right images in a pair, under the
Number column click the pair of your choice and click Switch
Pairs. To interchange the left and right images in all the pairs,
click Switch All Pairs.
If you chose Maximum Overlapping Pairs or All Overlapping
Pairs, the left and right images in the pair may be in the wrong order,
meaning that the left image is on the right and vice versa. This
situation will not affect DEM generation, but it will cause some
visually disturbing effects if you try to view the epipolar pair in threedimensions (3-D). Our brains are trained to interpret the images seen
from our left and right eyes in a certain way. If the images are in the
wrong order, we cannot compensate for the error so, for example, we
may see mountains that look like valleys instead.
7. You can limit the amount of memory used for generating the epipolar
pairs to allow other tasks to be completed. In Working Cache, type
the amount of RAM that you want to allocate to create the epipolar
pairs.
4. Under Left Image and Right Image, click Channels and type the
channel(s) that you want to use or click All to select all the available
channels.
8. In Down Sample Factor, type the number of image pixels and lines
that will be used to calculate one epipolar image pixel. For example,
typing “2” means that two adjoining pixels and two adjoining lines will
form one pixel in the epipolar image.
5. Click Add Epipolar Pairs To Table to record the pair(s) under
List of Epipolar Pairs. If you selected User Select, repeat steps 3
and 4 until you have recorded all the pairs that you want.
9. In Down Sample Filter, click the method used to determine the value
of the epipolar image pixel when the Down Sample Factor is greater
than 1. Click one of the following:
6. Under List of Epipolar Pairs, the pairs with a check mark in the
Select column will be converted into epipolar pairs. You can modify
your choices by using the following:
70
• Average to assign the average image pixel value to the epipolar
image pixel. The average is obtained by adding the image pixel
PCI Geomatics
Extracting Digital Elevation Models from Epipolar Pairs
values that will become one epipolar image pixel and dividing
that value by the number of image pixels used in the sum.
• Median to assign the median value of the image pixels to the
epipolar image pixel. The median is obtained by ranking the
image pixels that will become one epipolar image pixel according
to brightness. The median is the middle value of those image
pixels, which is then assigned to the epipolar image pixel.
• Mode to assign the mode value of the image pixels to the epipolar
pixel. The mode is the image pixel value that occurs the most
frequently among the image pixels that will become one epipolar
image pixel.
10. Under Processing Start Time, click Start Now or Start at
(hh:mm) and set the time when you want the operation to begin
(within the next 24 hours).
11. Click one of the following:
• Generate Pairs to begin the process following the time set under
Processing Start Time. Use this option if you are using the
epipolar pairs for 3-D Feature Extraction. If you are using the
epipolar pairs for Automatic DEM Extraction, you can either use
this option or Save Setup.
• Save Setup to save the options chosen for batch processing with
Automatic DEM Extraction. When Save Setup is selected, the
option set under Processing Start Time is disregarded. For
more information, see “Extracting Digital Elevation Models from
Epipolar Pairs” on page 71.
12. Click Close.
Next step in your project . . .
If you are using the epipolar images to generate a DEM, see “Extracting
Digital Elevation Models from Epipolar Pairs” on page 71.
If you are using the epipolar images for 3-D Feature Extraction, see
“Understanding 3-D Stereo Viewing and Editing” on page 81.
OrthoEngine User’s Guide
Extracting Digital Elevation Models from
Epipolar Pairs
The process of generating a digital elevation model (DEM) consists of
several steps:
• Convert the raw images into epipolar pairs.
Epipolar images are stereo pairs that are reprojected so that the left
and right images have a common orientation, and matching features
between the images appear along a common x axis.
• Extract DEMs from the overlap between the epipolar pairs.
The resulting DEMs are called epipolar DEMs. They are not
georeferenced at this stage.
• Geocode the epipolar DEMs and stitch them together to form one
DEM.
The result is one DEM reprojected to the ground coordinate system.
DEMs usually contain poorly correlated areas. You can correct these
areas before or after the DEMs are geocoded. Each approach has its
advantages.
Editing the DEM before it is geocoded:
The epipolar pair and its corresponding epipolar DEM are contained in
a single file. When you open the file in 2D DEM Editing, you can select
both the image channel and the epipolar DEM channel so you can
switch back and forth between them in the viewer. The image will help
you identify features in the DEM that need correction.
For example, you can switch between the image and the epipolar DEM
to delineate the border of a lake, adjust the profile of a shoreline, or
clean up its edges.
After you generate the epipolar DEMs, you can edit them (see “Editing
the Digital Elevation Model” on page 75), geocode them (see
“Geocoding a Digital Elevation Model” on page 79), and then integrate
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Chapter 6 - Generating Digital Elevation Models
them into one DEM (see “Using Rasters to Generate a Digital
Elevation Model” on page 64).
Editing the DEM after it is geocoded:
When you use the Automatic DEM Extraction window to complete
the entire process in one operation, OrthoEngine builds a model based
on all the selected epipolar pairs and uses that model when the DEMs
are geocoded. The geocoded DEMs are automatically stitched together
and saved in a file. Because OrthoEngine uses a model to process all
the epipolar pairs, the resulting integrated geocoded DEM is slightly
more accurate than if you completed the process manually.
You can edit the geocoded DEM using 2D DEM Editing (see “Editing
the Digital Elevation Model” on page 75), however, the file will not
include the raw image.
To extract a digital elevation model:
1. Prepare the epipolar pairs. See “Creating Epipolar Images” on page 69.
2. On the OrthoEngine window in the Processing Step list, select
DEM From Stereo.
3. Click
the Extract DEM automatically icon.
4. On the Automatic DEM Extraction window under Stereo Pair
Selection, click in the Select column to select epipolar pairs or click
Select All to select all the epipolar pairs that appear in the list.
If the epipolar pairs do not exist or are not available, OrthoEngine
will automatically generate the epipolar pairs using the options that
you saved in the Generate Epipolar Images window.
5. In the Minimum Elevation and Maximum Elevation boxes, type
the estimated elevation for the terrain in the stereo pair.
The minimum and maximum elevations are used to estimate the
search area for the correlation. This increases the speed of the
correlation and reduces errors. If the resulting DEM contains failed
values on peaks or valleys, increase the range.
72
6. In the Failure Value box, type the value used to represent the failed
pixels in the resulting DEM.
Specifying a failure value will assist you in interpolating these pixels
when you edit the DEM.
7. In the Background Value box, type the value used to represent the
“No Data” pixels in the DEM.
The “No Data” or background identifies the pixels that lie outside the
extracted DEM overlap area so they are not mistaken for elevation
values.
8. In the Pixel Sampling Interval list, click the number of image pixels
and lines (sampling frequency) that will be used to extract one DEM
pixel. For more information, see “Understanding Pixel Sampling and
DEM Detail” on page 73.
Using a Pixel Sampling of one pixel is not recommended to derive a
DEM for RADARSAT data, because of the difficulties with
correlating the speckle inherent in all SAR data.
9. In the DEM Detail list, click the level of detail that you want in the
extracted DEM. For more information, see “Understanding Pixel
Sampling and DEM Detail” on page 73.
10. Select Use Clip Region if you want to process only the area
determined in the Define Clip Region window, which results in
smaller DEMs and faster processing. To create the Clip Region, see
“Defining a Clip Region” on page 30.
11. Select Fill Holes And Filter if you want to enhance the output quality
of the DEM by interpolating the failed areas and filtering the elevation
values automatically.
12. Select Create Score Channel if you want to generate an additional
image channel to represent the correlation score for each DEM pixel.
The correlation score will help you to identify pixels where
correlation to the ground was weak or failed, which gives you a truer
impression of the success of the operation.
PCI Geomatics
Understanding Pixel Sampling and DEM Detail
13. Select Delete Epipolar Pair After Use if you want to delete the
epipolar pairs from the disk to save space after the DEM is generated.
14. Under Geocoded DEM, select Create Geocoded DEM if you want
to geocode and merge the epipolar DEMs.
However, if you want to edit the DEM before it is geocoded DO NOT
select Create Geocoded DEM, and skip to step 19.
15. To save space, you can select Delete Epipolar DEM After Use to
delete the epipolar DEM from the disk after the geocoded DEM is
generated.
16. In the Output Filename box, type the path for the geocoded DEM file
or click Browse to add it to an existing geocoded DEM file.
existing geocoded DEM and the one being added to the file. This
option is only useful if you select Create Score Channel.
19. Under Extraction Start Time, click Start Now or Start at
(hh:mm) and set the time when you want the operation to begin
(within the next 24 hours).
20. Click Start DEM Extraction.
21. Click Close.
Next step in your project . . .
To edit the DEM, see “Opening the Digital Elevation Model Editing
Windows” on page 74.
17. To determine the extents of the DEM, select one of the following:
• In Upper Left, Lower Right, and Resolution, type the new
values in the X and Y boxes that you want to change.
• In DEM Bounds, click All Photos to use the extents of all the
images in the Stereo Pair Selection table as the extents for the
DEM or click Selected Photos to use only the extents of the
images checked under the Select column. Click Recompute to
recalculate the extents.
18. As the epipolar pairs are generated and geocoded, they are added to the
geocoded DEM file. When a new geocoded DEM is added to the file
and it overlaps an existing geocoded DEM, you must choose a method
to determine which pixel value will be used. In the Output Option
list, click:
• Use Last Value to replace the pixel values in the overlap area in
the existing geocoded DEM by the pixel values of the geocoded
DEM being added to the file.
• Average to replace the pixel values in the overlap area by the
average pixel values between the existing geocoded DEM and the
one being added to the file.
Understanding Pixel Sampling and DEM
Detail
DEM Extraction uses image correlation to find matching features on
the left and right image of a stereo pair. The best way to find these
matching features is a hierarchical approach using a pyramid of
reduced resolution images.
The first attempt at correlation is performed on very coarse versions of
the images. This enables OrthoEngine to match prominent features
accurately, which forms the basis for further correlation attempts. The
next correlation attempts are performed to match finer features on
higher and higher resolution versions of the images. Finally,
correlation is performed on images at full resolution, which provides
the highest precision for the terrain in the digital elevation model
(DEM). This correlation technique speeds up the image correlation
process and reduces the number of mismatches.
DEM Detail and Pixel Sampling control the type of DEM that you want
to produce:
• Highest Score to replace the pixel values in the overlap area by
the pixel value with the highest correlation score between the
OrthoEngine User’s Guide
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Chapter 6 - Generating Digital Elevation Models
DEM Detail determines how precisely you want to represent the
terrain in the DEM. Selecting High, Medium or Low determines at
which point in correlation process you want to stop. Low means that
the process stops during the coarse correlation phase on aggregated
pixels so the level of detail in the DEM will be quite low. High means
the process continues until correlation is performed on images at full
resolution.
Pixel Sampling controls the size of the pixel in the final DEM relative
to the input images. The higher the number you choose, the larger the
DEM pixel will be, and the faster the DEM is processed.
Figure 6.4: Explaining Pixel Sampling
but need a smoother DEM that represents the terrain better (low DEM
Detail).
Opening the Digital Elevation Model
Editing Windows
To open the DEM editing windows:
1. On the OrthoEngine window in the Processing Step list, select
Import & Build DEM or DEM From Stereo.
2. Click
the Manually edit generated DEM icon.
3. On the Image/DEM File window, click the DEM file and click
Open.
4. On the File window under Database Channels, click the DEM
channel.
If you are editing an epipolar DEM, both an image channel and a
DEM channel may be available. Click the image channel for channel
1 and then click the DEM channel for channel 2. Switching back and
forth between the image and the DEM in the viewer can help you
identify features in the DEM that need correction.
Depending on the results you are looking for, you can use different
combinations of these two features. For example, you may want to have:
5. Under Database Window Selection, you can limit the DEM to a
specific size. Click Preview and drag the white guidelines to frame the
area that you want. Click Overview to reset the Database Window
Selection window to the default.
• A low resolution DEM (high-numbered Pixel Sampling) if the terrain is
fairly flat, but retain high precision for the pixel values in the DEM
(high DEM Detail).
6. Click Load & Close.
• A high resolution DEM (low-numbered Pixel Sampling) if your
imagery is coarse such as SPOT or RADARSAT data, and select low
DEM Detail to speed up the process or produce a smooth DEM.
Next step in your project . . .
For the next step in your project, see “Editing the Digital Elevation Model”
on page 75.
• A full resolution DEM (Pixel Sampling of 1) for aerial photographs,
which would contain very fine features such as light posts and bushes,
74
PCI Geomatics
Switching Between the Image Channel and the DEM
Switching Between the Image Channel
and the DEM
If you are editing an epipolar DEM, the file may contain both an image
channel and a DEM channel, which can be opened in the viewer (see
“Opening the Digital Elevation Model Editing Windows” on page 74).
You can switch back and forth between the channels to identify
features in the DEM that need correction. Select Show Image to view
the image. Select Show DEM to view the DEM.
Editing the Digital Elevation Model
Digital elevation models (DEMs) may contain pixels with failed or
incorrect values. You edit the DEM to smooth out the irregularities and
create a more pleasing DEM. For example, areas such as lakes often
contain misleading elevation values so setting those areas to a constant
value improves your model. For some suggestions on how to handle
common situations, see “Applying Tool Strategies for Common
Situations in Digital Elevation Models” on page 78.
To edit the DEM:
1. Open the 2D DEM Editing windows. For more information, see
“Opening the Digital Elevation Model Editing Windows” on page 74.
2. In the Failed box, type the value assigned to the pixels that have no
elevation values because the image correlation failed. Some features
will not be accessible unless you enter the failed value.
3. In the Background box, type the value assigned to the area outside the
DEM, which is usually a maximum or minimum value such as -150 or
-999999. Some features will not be accessible unless you enter the
background value.
4. Create a mask. For more information, see “Creating a Mask” on
page 75.
page 77, and “Applying Tool Strategies for Common Situations in
Digital Elevation Models” on page 78.
6. Click Save DEM back to file.
You can save the DEM at any time during the editing process. The
first time that you save the DEM, you can choose to create a new
channel for the edited DEM or to replace the original DEM.
Next step in your project . . .
If you have not already geocoded the DEM, see “Geocoding a Digital
Elevation Model” on page 79. If you have geocoded the DEM, your DEM is
finished.
Creating a Mask
A mask identifies specific areas that you want to edit. The mask does
not change the values in the area that it covers. To edit the area under
the mask, see “Replacing the Elevation Values Under a Mask” on
page 76.
Feature
Purpose
Procedure
Trace
Draw an irregular line
Click Trace and drag the
cursor over the area that you
want to edit.
Trace&Close
Draw an irregular
shape
Click Trace&Close and drag
the cursor around the area
you want to edit. The shape
closes automatically.
PolyLine
Draw a line of straight
segments
Click PolyLine and click in
the viewer over the area you
want to edit.
5. Edit the DEM. For more information, see “Replacing the Elevation
Values Under a Mask” on page 76, “Filtering and Interpolating” on
OrthoEngine User’s Guide
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Chapter 6 - Generating Digital Elevation Models
Feature
Purpose
Procedure
Feature
Purpose
Procedure
Polygon
Draw a polygon
Click Polygon and click in
the viewer around the area
you want to edit. Click
Polygon again to close the
polygon.
Clear Mask
Erase the mask
Click Clear Mask to remove
the mask from the viewer.
Show Mask
Show or hide the
mask
Click Yes to display the mask
in the viewer. Click No to
hide the mask. You can edit
the values under the mask
whether the mask is visible
or not.
Change the color of
the mask
Select a color from the list
beside Show Mask.
Determines the
thickness of the mask,
Type or select the size that
you want.
[email protected]
Fill the polygon or
irregular shape
Make sure that the mask that
you want to fill is closed. If
the shape or polygon is
open, the fill will cover the
entire DEM.
Click [email protected] and click
the mask that you want to fill.
If you want to fill several
masks consecutively, click
[email protected] and right-click
the masks.
Fill Failed
@Cursor
Create a mask over
an area of pixels with
failed values
Click Fill [email protected]
and click the area that you
want to fill.
If you want to fill several
areas consecutively, click Fill
[email protected] and rightclick the masks.
If the area does not fill with a
mask, the area may not
contain failed values or you
may have set the failed value
incorrectly.
Fill all Failed
76
Create a mask over all
the failed values in the
DEM
Click Fill all Failed.
If masks do not appear, the
DEM may not contain failed
values or you may have set
the failed value incorrectly.
Line Drawing
Width
Replacing the Elevation Values Under a Mask
To replace the elevation values under a mask with a new
value:
1. Create a mask. For more information, see “Creating a Mask” on
page 75.
2. Under Area Fills Under Mask in the Value box, type the value that
you want to place under the mask.
3. Click Fill Using Value.
4. Click Clear Mask.
Tip
For example, you want to correct a lake in your DEM. You can create a
mask over the lake, find the lake‘s true elevation from a map, type the
elevation value in the Value box, and click Fill Using Value.
PCI Geomatics
Editing the Digital Elevation Model
To replace the elevation values under a mask with an
average value:
1. Create a mask. For more information, see “Creating a Mask” on
page 75.
2. Under Area Fills Under Mask, click Fill Using Average.
Average displays the average (mean) of all the elevation values
under the mask.
To bulldoze a line:
1. Under Bulldoze a Line in the Value box, type the value that you
want to use.
2. In the Bulldoze a Line Width list, type or select the thickness of the
line.
3. Click Bulldoze Using Value.
4. Drag the cursor over the area that you want to edit.
3. Click Clear Mask.
Tip
For example, you decide that a residential area in the DEM is too rough.
You can create a mask over the area and click Fill Using Average.
To replace the elevation values under several masks with
their average values:
You can create masks over several different areas and replace the
values under each mask with the average (mean) of all the elevation
values under each mask. Therefore, OrthoEngine calculates the average
under each mask independently and fills each area with its own
average.
1. Create several masks. For more information, see “Creating a Mask” on
page 75.
2. Click Fill Each Polygon with Polygon Average.
3. Click Clear Mask.
Bulldozing a Line
Bulldoze a Line is a combination of Trace and Fill Using Value. As you
drag your cursor over an area, the masked area is filled with the value
that you set.
OrthoEngine User’s Guide
Filtering and Interpolating
Use the filters available under Filtering and Interpolation to
eliminate failed or incorrect values in your DEM. You can apply each
filter repeatedly to achieve a cumulative effect, and in different
combinations to obtain the results that you want.
You can limit the effect of the selected filter to a specific area by
creating a mask and clicking Apply Under Mask or you can distribute
the effect throughout the DEM by clicking Apply to Entire DEM.
Noise Removal
Noise refers to pixels containing distorted or failed values. Since pixels
adjacent to failed pixels tend to contain incorrect values as well, Noise
Removal uses two filters to identify failed pixel values and their
surrounding pixels:
• The first filter calculates the average and variance of the eight elevation
values immediately surrounding each pixel, excluding failed and
background pixels. If the center pixel is more than two standard
deviations away from the average, it is replaced with the failed value.
• The second filter counts the number of failed values immediately
surrounding each pixel. If five or more failed pixels border the center
pixel, then the center pixel is also set to a failed value.
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Chapter 6 - Generating Digital Elevation Models
Erode Holes
Equalizing Pixel Values for Lakes
Since pixels adjacent to failed pixels tend to contain incorrect values
as well, the Erode Holes filter replaces the eight pixels around each
failed pixel with the failed value. When you apply the filter under a
mask, the mask will enlarge to cover any additional pixels replaced by
the failed value.
Since lakes do not have features that can be used for matching during
DEM extraction, lakes in the DEM often contain failed pixel values or
incorrect elevation values.
Median
1. Create a mask over the lake.
The Median filter ranks the pixel values within a five-by-five pixel
frame according to brightness. The median is the middle value of those
image pixel values, which is then assigned to the pixel in the center of
the frame.
2. Identify the elevation of the lake.
Smooth
The Smooth filter is a Gaussian filter that calculates the weighted sum
of all the pixels in a three-by-three pixel frame and assigns the value to
the center pixel in the frame. Failed and background pixel values are
not replaced by the filter and are not used in the Gaussian calculation.
To adjust a lake’s pixel values:
3. Type the value in the Value box beside Fill Using Value.
4. Click Fill Using Value.
This sets the entire lake to a flat surface at the correct elevation.
5. Click Clear Mask.
To adjust the pixel values for several lakes:
1. Select Interpolate and click Apply Under Mask.
Interpolate
The elevation of the lake is interpolated using the values along the
shoreline.
The Interpolate filter replaces failed values with an estimate weighted
by distance calculated from the valid pixels surrounding the failed
pixel(s). The algorithm used to calculate the estimate is adequate for
small areas of less than 200 pixels, but is not recommended for larger
areas.
2. Click Fill Each Polygon with Polygon Average.
Applying Tool Strategies for Common
Situations in Digital Elevation Models
3. Click Clear Mask.
Editing digital elevation models (DEMs) requires an understanding of
the desired results combined with insightful artistry to achieve the
desired results. Every DEM presents a variety of problematic
situations. The following examples present the most common problems
and provide some methods to handle them.
78
The average elevation is calculated under each mask and applied to
the area. As a result, each lake has a flat surface of approximately the
correct elevation.
Compensating for Forests and Urban Areas
The repetitive textures of forests and urban areas often cause those
areas to contain a lot of failed values, noise and poorly correlated
elevation values.
PCI Geomatics
Geocoding a Digital Elevation Model
To compensate for forests or urban areas:
To remove noise from the DEM:
1. Create a mask over the area.
1. Make sure all large bodies of water, such as lakes, have been fixed. See
“Equalizing Pixel Values for Lakes” on page 78
2. Type the failed value in the Value box beside Fill Using Value.
3. Click Fill Using Value.
This sets the area to the failed value.
4. Select Interpolate and click Apply Under Mask.
The elevation of the area is interpolated using the values along the
edge of the mask.
5. Click Clear Mask.
Neutralizing Cloud-Covered Areas
When clouds obscure a large area over rugged or mountainous terrain,
the area may be too complex to interpolate. To avoid confounding the
data, you can set the entire area to the background value.
2. Select Noise Removal and click Apply to Entire DEM.
3. Click Apply to Entire DEM again.
4. Select Interpolate and click Apply to Entire DEM.
5. Select Smooth and click Apply to Entire DEM.
6. Click Apply to Entire DEM again.
Geocoding a Digital Elevation Model
Geocoding means that you are reprojecting the epipolar digital
elevation model (DEM) to the ground coordinate system at a given
ground resolution.
Note
To neutralize the effect of cloud cover over rugged terrain:
1. Create a mask over the area.
2. Type the background value in the Value box beside Fill Using Value.
3. Click Fill Using Value.
This sets the area to the background value.
If you selected Create Geocoded DEM on the Automatic DEM Extraction
window, your epipolar DEMs are already geocoded.
To geocode the extracted DEM:
1. On the OrthoEngine window in the Processing Step list, select
DEM From Stereo.
4. Click Clear Mask.
2. Click
Dealing with Noise
3. Under Input DEM in the File box, type the path where the extracted
epipolar DEM is found or click Browse to select the file.
Noise is a random occurrence of irrelevant or miscorrelated values
distributed throughout the DEM, which reduces its accuracy. The
following procedure usually produces a satisfactory DEM, except for
areas containing large bodies of water such as lakes.
OrthoEngine User’s Guide
the Geocode Extracted DEM icon.
4. In the DEM Channel list, click the DEM channel or click Select to
view the choices and choose a channel.
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Chapter 6 - Generating Digital Elevation Models
5. In the Failure Value box, type the value used to represent the failed
pixels in the input DEMs.
6. In the Background Value box, type the value used to represent the
background.
The background identifies the pixels that lie outside the DEM so they
are not mistaken for elevation values.
7. Under Input Window, click:
To export the DEM to a text file:
1. On the OrthoEngine window in the Processing Step list, select
DEM From Stereo.
2. Click
the Export the Geocoded DEM to text file icon.
3. Under Input DEM in the File box, type the path where the DEM is
found or click Browse to select the file.
• Full Image to geocode the entire DEM.
4. In the DEM Channel list, click the DEM channel or click Select to
view the choices and choose a channel.
• Window to geocode a specific area of the DEM. In the Offset
boxes, type the pixel and line coordinates of the upper-left corner
of the area. In the Size boxes, type the number of pixels and lines
to specify its size.
5. In the Failure Value box, type the value used to represent the failed
pixels in the input DEM.
8. Under Output DEM in the File box, type the path where the
geocoded DEM is saved or click Browse to select a location.
9. In the Pixel Spacing box, type the output pixel size in the units (meters,
feet, or degrees) used in the project.
10. In the Fill Holes list, select Yes if you want to enhance the output
quality of the DEM by interpolating the failed values automatically.
Select No to set all the failed pixels to the background value in the
output DEM.
11. Click Geocode DEM.
Exporting a Digital Elevation Model to a
Text File
You can export the digital elevation model (DEM) into a text file. The
file will contain the x and y coordinates and the gray levels
representing the elevation values.
6. In the Background Value box, type the value used to represent the
background.
7. Under Input Window, click:
• Full Image to export the entire DEM.
• Window to export a specific area of the DEM. In the Offset
boxes, type the pixel and line coordinates of the upper-left corner
of the area. In the Size boxes, type the number of pixels and lines
to specify its size.
8. In the Spacing box, type the sampling frequency of the pixels exported
to the text file. OrthoEngine extracts the x, y, and z coordinates of every
nth pixel and saves them in a file using an ASCII format. For example,
typing 1 in the Spacing box generates a file with the coordinates of all
the pixels in the DEM.
9. Under Output DEM in the File box, type the path where you will
save the file or click Browse to select a location.
10. Select Require Supresoft DEM format if you are using the file with
Supresoft products.
11. Click Export DEM.
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PCI Geomatics
CHAPTER
7
Editing Features in 3-D Stereo
Understanding 3-D Stereo Viewing and
Editing
Your eyes see your surroundings from slightly different positions so
each eye observes objects from different angles. Your brain receives
this information and unites these different views into one threedimensional (3-D) image. This allows you to perceive the depth and
height of the objects in your surroundings.
Since your brain performs this process far better and faster that any
machine, OrthoEngine’s 3-D editing features take advantage of your
natural stereoscopic vision to provide an intuitive environment for you
to interpret images.
Objects with height appear to lean away from the center of the image.
This is commonly referred to as relief displacement. If you digitize
features from the image (even an orthorectified image), the x and y
coordinates will be offset from their true positions because of relief
displacement. By digitizing features in 3-D stereo, your eyes will
compensate for the relief displacement. As a result you collect the
correct planimetric positions (x and y coordinates) and accurate
elevations (z coordinates) for the features.
By using an anaglyph display and 3-D glasses or special stereo viewing
hardware, you can present your left eye with only the left image and
your right eye with only the right image from the stereo pair. Your
brain will automatically correct the geometric effects of sensor
geometry and relief displacement.
Similarly, the stereo cursor is actually made of two cursors: one only
displayed to the left eye, and the other only displayed to the right eye.
By adjusting the difference in x coordinate, or parallax, between the
left and right cursors, you control the apparent height of the cursor.
This way, you can position the cursor not only in x and y, but also in z.
You can more easily recognize the features, measure and record
accurate coordinates for the features, and collect planimetrically
correct vectors in the 3-D environment.
Next step in your project . . .
See “Examining the 3-D Feature Extraction Work Flow” on page 83.
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Chapter 7 - Editing Features in 3-D Stereo
Viewing in 3-D Using Anaglyph Technology
Anaglyph technology uses a standard monitor to simulate a threedimensional (3-D) view of the images. The left image is displayed in
red and the right image is displayed in blue. When you wear red/blue
anaglyph glasses, the red lens filters out the blue image and the blue
lens filters out the red image so each eye is presented with a different
image from the stereo pair.
The advantages of using this technology:
• The technology is available on all platforms.
• No special hardware is needed other than the inexpensive 3-D glasses.
• You can use single or double monitor configurations.
• You can set your monitor to full resolution.
The disadvantages of using this technology:
• The images must be in grayscale.
• The range of colors for viewing the vectors and the cursor is limited.
• You may experience eye strain or fatigue.
To reduce eyestrain and fatigue, take frequent breaks, arrange your
lighting to minimize glare and reflections on your screen, and use the
correct settings for your monitor. Incorrect settings on your monitor
can cause a noticeable screen flicker, particularly on larger screens.
Also, you can alleviate eye strain by readjusting the parallax between
your images, see “Adjusting the Alignment in the Stereo Viewer” on
page 85.
Viewing in 3-D Using OpenGL Technology
OpenGL technology uses special stereo hardware, such as specialized
graphics cards and shutter glasses or polarizing monitors and glasses,
to filter the images so that each image is displayed to the appropriate
eye.
82
Shutter glasses use high-speed liquid crystal shutters to block the view
from one eye or the other in sync with the monitor displaying
alternating images from the stereo pair. Polarizing monitors and
glasses function in a similar way.
The advantages of using this technology:
• You can view the images in full color.
• It provides a more natural stereo viewing experience.
• You may experience considerably less eye strain.
• You can use single or double monitor configurations.
• The 3-D effect is superior to the anaglyph technology.
The disadvantages of using this technology:
• You need additional hardware to take advantage of this technology.
• You may need to set your monitor at a lower resolution due to extra
demands on the video card.
Since lower color depths can cause artifacts and refresh difficulties
with OpenGL technology, we recommend that you set your monitor to
32-bit or Full Color Display. For effective stereo viewing, the
monitor’s frequency should be at least 100Hz, and the resolution
should be greater than 1024 by 768, or as permitted by the graphics
card.
Using Epipolar Images for 3-D Stereo
Editing
Using epipolar images while editing in three-dimensional (3-D) stereo
editing can greatly improve your view of the images, and can reduce
the need to manually align the images. For more information, see
“Creating Epipolar Images” on page 69.
PCI Geomatics
Reducing Eyestrain
Reducing Eyestrain
Many people experience difficulty such as eyestrain and fatigue when
they work in a 3-D environment. The following are a few tips to avoid
discomfort:
Constantly adjust the focus in the 3-D viewer
Normally, the cursor and the screen share the same focus. In the 3-D
viewer, however, the cursor can move not only in x and y, but also in
z. This means that the cursor can appear as if it is floating off the screen
or behind the screen. While performing feature extraction, press F or
F3 to refocus your images to the elevation of the cursor. Press F4 to
refocus and center images in the viewer.
Minimize the offset between your left and right images
Raw images in the 3-D viewer do not usually align. Epipolar images
usually align, but might need some adjustments. Misaligned images
can make it difficult or impossible to see in stereo, and it can put stress
on your eyes. As you move from one area to another in the stereo pair,
press I, J, K, or M to shift the right image to align with the left.
Remember to adjust the elevation of your cursor
Examining the 3-D Feature Extraction
Work Flow
To create or edit vectors in 3-D:
1. Select a stereo pair, see “Selecting the Stereo Pair” on page 83.
2. Adjust the images in the 3-D viewer, see “Adjusting the Alignment in
the Stereo Viewer” on page 85.
3. Create a layer, see “Creating a Layer” on page 85, or import a layer, see
“Loading a Layer” on page 87.
4. Draw vectors, see
• “Adding Points to a Layer” on page 88
• “Adding Lines to a Layer” on page 88
• “Adding Polygons to a Layer” on page 89
5. Edit vectors, if necessary, see “Using the Vector Editing Tools” on
page 90.
6. Type attributes for the vectors, see “Designing the Attribute Table” on
page 92.
If the two crosshairs of the stereo cursor do not coincide, the cursor is
probably far above or below the terrain. Press G or F2 to move the
cursor to the ground elevation.
7. Save the layers, see “Saving a Layer” on page 93.
Recenter the images
Selecting the Stereo Pair
Working in the middle of the 3-D viewer is easier on your eyes. Since
the 3-D viewer and the normal screen display information differently,
your eyes may have difficulty adjusting to both environments at the
same time. Press R or F1 to recenter the cursor and images.
8. Click Close.
As described in “Understanding 3-D Stereo Viewing and Editing” on
page 81, your eyes are the key to viewing in three dimensions (3-D).
Note
Having the stereo images in the wrong order (left image on the right and
vice versa) will not affect processing, but it will cause some visually
disturbing effects if you try to view the epipolar pair in three-dimensions (3D). Our brains are trained to interpret the images seen from our left and right
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Chapter 7 - Editing Features in 3-D Stereo
eyes in a certain way. If the images are in the wrong order, we cannot
compensate for the error so, for example, we may see mountains that look
like valleys instead. If this occurs, select the images in the opposite order.
To select a 3-D stereo pair:
1. On the OrthoEngine window in the Processing Step list, select 3-D
Operations.
2. Click
the 3-D feature extraction icon.
3. On the 3-D Stereo Pair Selection window under Project Pair
Overview, click the crosshairs of the image that will be displayed to
your left eye.
• OpenGL to display in a single window the images alternately in
black and white or in color. Special stereo hardware such as
specialized graphics cards and shutter glasses or polarizing
monitors are used to filter the images so that each image is only
displayed to the appropriate eye. The OpenGL display method
provides a more natural stereo viewing experience than the
Anaglyph method, but it requires more expensive hardware.
7. Click Load Pair.
Note
To select a new stereo pair from the 3-D Viewing window, click Select
Stereopair to open the 3-D Stereo Pair Selection window and continue
with step 3 of Selecting the Stereo Pair.
All the crosshairs of the images that overlap the selected image appear
in blue under Stereo Pair Detail.
4. Under Stereo Pair Detail, click the crosshairs of the overlapping
image that will be displayed to your right eye.
5. Click Uncorrected Image to select the raw images or click Epipolar
Image to select an epipolar pair.
If epipolar images exist for the pair that you selected, the option
Epipolar Image will become available. Using epipolar images while
editing in 3-D stereo produces a sharper stereo view over the entire
area of the image, and reduces the need to manually align the images.
For more information, see “Creating Epipolar Images” on page 52.
6. In the Stereo Mode list, click the type of viewing display that you are
using. OrthoEngine will automatically search for the OpenGL libraries,
but will not confirm the presence of the required stereo viewing
hardware. If the OpenGL libraries are present, both Anaglyph and
OpenGL options will be available. Click:
• Anaglyph to display the one image in red and the other in blue.
To view the images in 3-D, you must wear a pair of 3-D glasses,
which has one red lens and one blue lens.
84
Next step in your project . . .
See “Navigating Within the 3-D Viewing Window” on page 84.
Navigating Within the 3-D Viewing
Window
To begin working in the viewer, you must switch from the mouse
pointer to the stereo cursor.
The stereo cursor is made of two cursors: one is only displayed to the
left eye, and the other is only displayed to the right eye. Your brain
receives this information and unites these cursors into one threedimensional (3-D) cursor. This allows you to perceive the depth and
height of the objects in the viewer. By adjusting the difference in x
coordinate, or parallax, between the left and right cursors, you control
the apparent height of the cursor. This way, you can position the cursor
not only in x and y, but also in z.
The stereo cursor remains in the viewer. When you move outside the
viewer, the stereo cursor is left behind in the viewer and the pointer is
PCI Geomatics
Adjusting the Alignment in the Stereo Viewer
activated. When the pointer returns to the viewer, the stereo cursor
resumes control and the pointer disappears.
However, if you want the stereo cursor to remain on a specific point in
the viewer while you move to select a tool, you must switch from the
stereo cursor to the pointer without moving the mouse.
To switch between the pointer and the stereo cursor:
1. Move the pointer to the viewer and press ESC.
The pointer disappears and the stereo cursor is activated.
2. Move the stereo cursor to a feature in the image and press ESC.
The stereo cursor remains on the feature and the pointer reappears.
Next step in your project . . .
See “Adjusting the Alignment in the Stereo Viewer” on page 85.
Adjusting the Alignment in the Stereo
Viewer
When the stereo pair of images is loaded into the viewer, you may need
to adjust the alignment between the images. Raw images in particular
may require significant adjustments. Misaligned images can make it
difficult or impossible to see in stereo, and it can put stress on your
eyes.
To align the images:
Moving the Stereo Cursor Pixel by Pixel
Press I, J, K, or M to shift the right
image to align with the left.
Press the keyboard arrow keys to move the stereo cursor screen pixel
by screen pixel.
To select a different stereo pair:
Press CTRL + the ARROW keys to move the stereo cursor 10 screen
pixels at a time.
Click Select Stereopair and start with
step 3 in “Selecting the Stereo Pair” on
page 83.
Moving the Stereo Cursor to Different Elevations
By adjusting the difference in x coordinate, or parallax, between the
left and right cursors, you control the apparent height of the cursor.
This way, you can position the cursor not only in x and y, but also in z.
To change the elevation of the stereo cursor:
• Rotate the wheel button.
• Press Z to move the stereo cursor to higher elevations, and press X to
move the stereo cursor to lower elevations.
• Press G to snap to ground, which means to automatically move the
stereo cursor to the three-dimensional surface (z coordinate) of a feature
at the cursor’s current position, such as a field, a roof top, or a tree top.
OrthoEngine User’s Guide
Next step in your project . . .
See “Creating a Layer” on page 85 or “Loading a Layer” on page 87.
Creating a Layer
The bounds are set by default to the combined extents of the stereo pair
displayed in the three-dimensional (3-D) viewer. You can change the
default and make the bounds smaller or larger than the default. If you
edit a layer with data from another area in the project, the bounds
automatically enlarge to cover all the data.
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Chapter 7 - Editing Features in 3-D Stereo
For example, you might want to create one layer that covers the entire
project. By loading that layer and adding vectors to the layer for each
stereo pair, you will end up with a vector layer for the entire project.
Next step in your project . . .
See “Adding Points to a Layer” on page 88, “Adding Lines to a Layer” on
page 88, and “Adding Polygons to a Layer” on page 89.
To create a layer:
1. Under Vector Layer Information, click New Layer.
2. On the Create New Layer window in the Name box, type a label for
the new layer.
3. In the Description box, type a description of what the layer will
contain.
4. Under Georeferencing Info, the projection is set by default. You can
change the projection, however, this may significantly affect the
performance.
For information about changing the projection, see “Changing the
Projection When Creating a New Layer” on page 86.
The bounds are set by default to the combined extents of the selected
stereo pair. If you do not want to change the bounds, go to step 8.
5. In the Bounds list, click Geocoded to enter the bounds in
georeferenced units or click Geographic to use Longitude/Latitude
units.
6. In the Upper Left boxes, type the coordinates of the upper left corner
of the layer.
7. In the Lower Right boxes, type the coordinates of the lower right
corner of the layer.
8. Click Accept.
The new layer appears in the Vector Layer Information table.
Changing the Projection When Creating a New Layer
The projection of the new layer is set to the project's output projection
by default. We recommend that you accept the default projection.
Changing the projection will cause OrthoEngine to re-project the file on-the
-fly, which can significantly hinder the performance.
Make sure you save your project and layers before attempting to add a
layer with a different projection.
To change the projection:
Type the projection string (for example, UTM 17 T D000) in the text
box beside the Earth Model button.
If you do not know the projection string:
1. Select a projection type from the list under Georeferencing Info.
(For UTM, State Plane Coordinate Systems (SPCS), or Other
projection types, additional windows may open automatically for you
to select the parameters to define the projection or click More to open
these windows. Select the parameters and click Accept.)
2. Click Earth Model.
3. Click either the Datum or Ellipsoid tab.
4. Click a datum or an ellipsoid.
5. Click Accept.
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PCI Geomatics
Loading a Layer
Loading a Layer
To change the priority of a layer:
You can import existing vector layers into your project. The files
containing the vector layers can be from any of the supported file
formats.
1. In the Vector Layer Information table, click the layer that you
want to move up or down in priority.
To import the vector layer:
1. Click Load Layer.
2. Click the Change Priority arrows to position the layer in the table.
The top row is the layer with the highest priority, and the bottom row
is the layer with the lowest priority.
2. Select the file and click Open.
Changing the Visibility of a Layer
3. Select the layer and click Load or Load & Close.
You can display or conceal vector layers individually or collectively.
The check mark in the Visible column in the Vector Layer
Information table indicates a layer that is displayed in the viewer.
The added layer becomes the active layer in the viewer.
Next step in your project . . .
See “Adding Points to a Layer” on page 88, “Adding Lines to a Layer” on
page 88, and “Adding Polygons to a Layer” on page 89.
Changing the Priority of a Layer
When two or more vector layer overlap, it may be difficult for you to
identify the vectors that you want. The layers in the 3-D viewer are
displayed one on top of the other in the same order as they appear in
the Vector Layer Information table.
As layers are added to the 3-D viewer, vectors are covered by other
vectors. The topmost row in the Vector Layer Information table
contains the layer with the highest priority, which means that its
vectors are not covered by any other layer.
Moving the layer that you are working on to the highest priority in the
3-D viewer can help you to see the vectors on that layer more clearly.
• To conceal or display an individual layer, right-click in the Visible
column of the layer.
• To conceal all the layers in the Vector Layer Information table, click
Hide All.
• To display all the layers in the Vector Layer Information table, click
Show All.
Changing the Color of the Vectors in a
Layer
You can select the color of each vector layer. Most of the colors are
compatible with the anaglyph viewer, however, some colors are easier
to see than others.
To change the color of a vector layer:
1. Click the layer that you want to change.
2. Right-click in the Color column of the layer.
3. Click the color that you want.
The check mark in the Visible column and the vectors of the layer
display the new color.
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Changing the Type of the Layer
The Type column in the Vector Layer Information table does not
affect the geometry or attributes of the vector layer. It simply provides
metadata that is saved into the layer.
To change the Type:
3. Position the stereo cursor on a feature. When you are satisfied with the
x and y positions, adjust the z position (elevation) of the stereo cursor.
You can also use Snap to Vertex or Snap to Line to position the
cursor. For more information, see “Using Snap to Vertex” on page 90
and “Using Snap to Line” on page 90.
Beneath the 3-D viewer, you can see the x, y, and z coordinates of the
stereo cursor’s location.
1. Click the layer that you want.
2. Right-click under Type.
4. Click to select the point.
Crosshairs indicate the location of the new point.
3. Click the label that you want for the layer:
• DEM Area
• DEM Building
• DEM Cliff
5. Repeat steps 3 and 4 until you have collected the points that you want
for the selected layer.
6. Click New Point to stop collecting points.
• DEM Contour
• DEM Gully
• DEM Points
• DEM Ridge
• Planimetric Area
Tip
When you are working with the stereo cursor in the 3-D viewer, you can:
press G to snap the stereo cursor to the ground
press P to activate and deactivate New Point.
For more shortcuts, see “Using Shortcuts in the 3-D Viewer” on page 94.
• Planimetric Line
• Planimetric Point
Adding Points to a Layer
You should complete the Attribute table each time you add a points,
lines, or polygons to the layer. For more information about the
Attribute table, see “Designing the Attribute Table” on page 92.
To add points to the selected layer:
1. Click New Point.
2. Move the mouse pointer to the 3-D viewer and press ESC to switch to
the stereo cursor.
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Next step in your project . . .
See “Designing the Attribute Table” on page 92.
Adding Lines to a Layer
You should complete the Attribute table each time you add points,
lines, or polygons to the layer. For more information about the
Attribute table, see “Designing the Attribute Table” on page 92.
To add lines to the selected layer:
1. Click New Line.
PCI Geomatics
Adding Polygons to a Layer
2. Move the mouse pointer to the 3-D viewer and press ESC to switch to
the stereo cursor.
3. Position the stereo cursor where you want to begin the line. When you
are satisfied with the x and y positions, adjust the z position (elevation)
of the stereo cursor and click to anchor the vertex. You can also use
Snap to Vertex or Snap to Line to position the cursor. For more
information, see “Using Snap to Vertex” on page 90 and “Using Snap
to Line” on page 90.
Beneath the 3-D viewer, you can see the x, y, and z coordinates of the
stereo cursor’s location.
Next step in your project . . .
See “Designing the Attribute Table” on page 92.
Adding Polygons to a Layer
You should complete the Attribute table each time you add points,
lines, or polygons to the layer. For more information about the
Attribute table, see “Designing the Attribute Table” on page 92.
To add polygons to the selected layer:
4. Move the stereo cursor to the next position. When you are satisfied
with the x and y positions, adjust the z position and click to anchor the
vertex.
5. Repeat step 4 until you have collected the vertices that you need to
form the line.
6. Click Accept or double-click when you collect the last vertex to
confirm the completion of the line.
After the new line is accepted, it will change from the highlight color
(white) to the color specified for the selected layer in the Vector
Layer Information table.
7. You can repeat steps 3 to 6 until you have collected the lines that you
want for the selected layer.
8. Click New Line to stop collecting lines.
Tip
When you are working with the stereo cursor in the 3-D viewer, you can:
press G to snap the stereo cursor to the ground
press ENTER to confirm the completion of the line
press L to activate and deactivate New Line.
For more shortcuts, see “Using Shortcuts in the 3-D Viewer” on page 94.
OrthoEngine User’s Guide
1. Click New Poly.
2. Move the mouse pointer to the 3-D viewer and press ESC to switch to
the stereo cursor.
3. Position the stereo cursor where you want to begin the polygon. When
you are satisfied with the x and y positions, adjust the z position
(elevation) of the stereo cursor and click to anchor the vertex. You can
also use Snap to Vertex or Snap to Line to position the cursor. For
more information, see “Using Snap to Vertex” on page 90 and “Using
Snap to Line” on page 90.
Beneath the 3-D viewer, you can see the x, y, and z coordinates of the
stereo cursor’s location.
4. Move the stereo cursor to the next position. When you are satisfied
with the x and y positions, adjust the z position and click to anchor the
vertex.
5. Repeat step 4 until you have collected the vertices that you need to
form the polygon.
Polygons will automatically close when they are accepted.
6. Click Accept or double-click when you collect the last vertex to
confirm the completion of the polygon and close the shape.
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After the new polygon is accepted, it will change from the highlight
color (white) to the color specified for the selected layer in the
Vector Layer Information table.
7. You can repeat steps 3 to 6 until you have collected the polygons that
you want for the selected layer.
2. Position the stereo cursor close to an existing vertex and click.
The cursor aligns with the vertex nearest to where you clicked.
3. Click Snap to Vertex. to turn off the feature.
You can turn on or off Snap to Vertex at any time while you are
collecting or editing vertices.
8. Click New Poly to stop collecting polygons.
Using Snap to Line
Tip
When you are working with the stereo cursor in the 3-D viewer, you can:
press G to snap the stereo cursor to the ground
press ENTER to confirm the completion of the polygon
press O to activate and deactivate New Poly.
For more shortcuts, see “Using Shortcuts in the 3-D Viewer” on page 94.
Next step in your project . . .
See “Designing the Attribute Table” on page 92.
Snap to Line places the cursor on the line nearest to where you click.
You can use it to quickly position new vertices or to move existing
vertices on the same layer.
Tip
When you are working with the stereo cursor in the 3-D viewer, you can:
press C to activate and deactivate Snap to Line.
For more shortcuts, see “Using Shortcuts in the 3-D Viewer” on page 94.
To snap to a line:
Using Snap to Vertex
Snap to Vertex places the cursor on the vertex nearest to where you
click. You can use it to quickly position new vertices or to move
existing vertices on the same layer.
1. Click Snap to Line.
2. Position the stereo cursor close to an existing vector and click.
The cursor aligns with the vector nearest to where you clicked.
3. Click Snap to Line. to turn off the feature.
Tip
When you are working with the stereo cursor in the 3-D viewer, you can:
press V to activate and deactivate Snap to Vertex.
For more shortcuts, see “Using Shortcuts in the 3-D Viewer” on page 94.
To snap to a vertex:
You can turn on or off Snap to Line at any time while you are
collecting or editing vertices.
Using the Vector Editing Tools
You can use the vector editing tools to move, change, and delete the
three-dimensional (3-D) vectors.
1. Click Snap to Vertex.
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PCI Geomatics
Using the Vector Editing Tools
To select a vector:
1. Move the pointer to the 3-D viewer and press ESC to switch to the
stereo cursor.
2. Click on the vector that you want to select or click the vector in the
Attribute table.
The vector is highlighted, and the stereo cursor is placed on the
nearest vertex. Only one vector can be selected at a time.
3. Use the Vector Editing tools:
• Insert Vertex
• Delete Vertex
• Delete Line
• Move
• Undo
2. Click the vertex that precedes the location where you want to place the
new vertex.
For information about how to select a vector, see “Using the Vector
Editing Tools” on page 90.
3. Click Insert Vertex or press INSERT.
4. Position the stereo cursor precisely on the location where you want to
place the new vertex. Adjust the position not only in x and y, but also in
z. You can also use Snap to Vertex or Snap to Line to position the
cursor. For more information, see “Using Snap to Vertex” on page 90
and “Using Snap to Line” on page 90.
5. Click to insert one or more vertices.
If the vector is not reacting as expected, click Undo and then Accept.
Try the process again by selecting the vertex beside the one you
selected before. Remember: vertices inserted into the vector are added
following the sequence that the original vector was created.
4. Click Accept or press ENTER to accept the change.
6. Click Insert Vertex or press INSERT to accept the additions.
Inserting a Vertex
To draw a line or a polygon, you click a series of vertices to form the
vector. The first vertex is the start point of the vector, and the last
vertex positioned is the end point. When you select an existing vector,
the stereo cursor snaps to the nearest vertex in that vector.
If you add a vertex to the existing line or polygon, the new vertex is
added at the location where you clicked. It will connect to the last
selected vertex and the next vertex following the sequence that the
original vector was created. If the last selected vertex is the end point
of a line, the vertices that you add will extend the line. If you add a
vertex to a point, the point is converted into a line.
To insert a vertex:
Deleting a Vertex
To delete a vertex:
1. Move the pointer to the 3-D viewer and press ESC to switch to the
stereo cursor.
2. Click the vertex that you want to remove.
3. Click Delete Vertex or press D.
The vertex is deleted, the vector adjusts automatically, and the action
is accepted.
4. To delete another vertex you must repeat the steps.
1. Move the pointer to the 3-D viewer and press ESC to switch to the
stereo cursor.
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Chapter 7 - Editing Features in 3-D Stereo
Deleting a Line or Polygon
To delete a line or polygon:
1. Move the pointer to the 3-D viewer and press ESC to switch to the
stereo cursor.
Reversing an Action (Undo)
Click Undo to cancel the last action made in the 3-D viewer. You can
restore the action by clicking Redo. However, you cannot cancel
actions that delete vectors or vertices, and Undo only functions for
actions that have not been accepted by clicking Accept, pressing
ENTER, and so on.
2. Select a vector.
For information about how to select a vector, see “Using the Vector
Editing Tools” on page 90.
3. Click Delete Line or press DELETE.
The vector is deleted, and the action is accepted.
Designing the Attribute Table
Each row in the Attribute table represents a vector on the selected
layer. Attributes are numeric or text values that describe the vector
such as a road name, the tree height, the date of data collection, or a
feature representation code used for cartographic production.
Moving a Vertex or a Point
Before you can add attributes to a vector, you need to define the
columns in the table. For each column you can define several
parameters, and you can change the parameters, except Type, at any
time:
To move a vertex:
To add a new column to the Attribute table:
1. Move the pointer to the 3-D viewer and press ESC to switch to the
stereo cursor.
1. Click Fields.
4. To delete another vector you must repeat the steps.
2. Click Move or press B.
3. Position the stereo cursor precisely on the location where you want to
place the vertex. Adjust the position not only in x and y, but also in z.
You can also use Snap to Vertex or Snap to Line to position the
cursor. For more information, see “Using Snap to Vertex” on page 90
and “Using Snap to Line” on page 90.
4. Click to move the selected vertex.
5. Click Accept or press ENTER to accept the move.
2. On the Vector Field Definition window, click Add Field.
3. In New Field window in the Name box, type the heading for the
column. The heading can contain any number of characters, including
valid ASCII printable characters.
4. In the Description box type a brief sentence describing the column or
a list of acceptable attribute values.
5. In the Data Type list select:
• Integer to define the field as containing positive or negative
whole numbers.
• Double to define the field as containing double-precision real
numbers.
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Assigning Attribute Values
• Float to define the field as containing single-precision real
numbers.
• Text to define the field as containing a string of text.
• Integer List to define the field as containing a list of positive or
negative whole numbers separated by commas.
6. In the Width list type the maximum field size. Although characters
that exceed the field size are not cut short in the .pix format, other
formats may discard the excess characters.
7. In the Precision list type the number of characters that can be
displayed after the decimal point. The definition only controls how the
value is displayed, and does not round-off the value you that type into
the field. This field is only valid when it is defined as a Double or Float
Data Type.
8. In the Justify list select Left Justify if you want to left align the
characters in the field or select Right Justify to right align the
characters. This field is not valid when it is defined as an Integer List
Data Type.
9. In the Default box type the default characters for the field, if desired. If
you change the default, previously existing shapes using the default
will not change.
10. Click Accept.
Assigning Attribute Values
After you have designed the Attribute table, you can enter the
attributes for each vector in the selected layer. For information about
how to design the Attribute table, see “Designing the Attribute Table”
on page 92.
To enter the values in the Attribute table:
1. In the Vector Layer Information table, select the layer containing the
vectors that you want, or select the feature in the viewer.
2. In the Attribute table each row represents a vector in the selected
layer. In the row of the vector that you want, click the field under the
column of the attribute you want to enter.
The corresponding vector is highlighted in the 3-D viewer.
3. If necessary, select the default data in the field and type the new value.
Press ENTER or click Accept.
The value is accepted and the default data is selected in the following
field automatically. Repeat step 3 until all the fields are satisfactory.
Next step in your project . . .
See “Saving a Layer” on page 93.
The new column is added to the Attribute table.
11. You can follow steps 3 to 10 to add another column or click Cancel.
12. On the Vector Field Definition window, click Close.
Next step in your project . . .
See “Assigning Attribute Values” on page 93.
OrthoEngine User’s Guide
Saving a Layer
You can add a new layer to an existing file or you can save the layer in
a PCIDSK (.pix), an ESRI Shape File (.shp), or an AutoCad (.dxf)
format. The layers that appear under Savable Vector Layers are the
layers that you have available in the stereo viewer. The layers that
appear under Database Vector Segments are the layers that are saved
in the file. If you close the stereo viewer, unsaved layers are discarded.
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Chapter 7 - Editing Features in 3-D Stereo
To save a layer:
Deleting a Layer
1. Click Save Layer.
You can remove a layer from the Vector Layer Information table
without deleting it from the disk.
2. Select a location.
3. Type the name for the layer in the File name box and select a format
from the Files of Type list.
To remove the layer from the table:
4. Click Save.
2. Click Delete Layer.
5. Under Savable Vector Layers, select the layer that you want to save.
3. Click Yes.
6. In the Description box, type a description that will help you identify
the contents of the layer.
1. Select the layer that you want to remove.
The layer will disappear from the table and from the 3-D viewer.
7. In the Name box, type a label for layer.
Using Shortcuts in the 3-D Viewer
8. Click Save or Save & Close.
You can use these shortcuts in any combination.
To replace an existing layer:
Table 3: Shortcuts for the 3-D viewer
Action
Keyboard
2. Select the file and click Save.
Switch between the pointer
and the stereo cursor
ESC
3. Under Database Vector Segments select the layer that you want to
replace.
Recenter at the stereo
cursor
R
F1
Snap to Ground
G
F2
Remove parallax
F
F3
1. Click Save Layer.
4. Under Savable Vector Layers click the layer that you want to save.
5. Click Save or Save & Close.
Note
If you selected a layer under Database Vector Segments, but you do
not want to replace the layer, click Create New Segment and type a
new description in the Description box and label in the Name box.
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Recenter and remove
parallax
Key Mouse
F4
Zoom In
PAGE UP
CTRL+click
Zoom Out
PAGE DOWN
CTRL+right-click
Move Image to the left
J
Move Image to the right
K
Move Image up
I
PCI Geomatics
Extracting Vector Points from a Digital Elevation Model
Table 3: Shortcuts for the 3-D viewer
Action
Keyboard
Move Image down
M
Move stereo cursor to a
higher elevation
Z
rotate the wheel
button forward
Move stereo cursor to a
lower elevation
X
rotate the wheel
button backward
Move the stereo cursor to
the right
RIGHT ARROW
Move the stereo cursor to
the left
LEFT ARROW
Move the stereo cursor
upwards
UP ARROW
Move the stereo cursor
downwards
DOWN ARROW
Accept
ENTER or
SPACE
double-click
Cancel
BACKSPACE
right-click
Undo
U
F5
New Point
P
F6
New Line
L
F7
New Polygon
O
F8
Snap to Vertex
V
F9
Snap to Line
C
F10
6. In the Background Value box, type the background pixel value.
Insert Vertex
INSERT
F11
7. Under Input Window, click:
Delete Vertex
D
F12
Delete Line
DELETE
Move
B
OrthoEngine User’s Guide
Key Mouse
Extracting Vector Points from a Digital
Elevation Model
You can extract vector points from a digital elevation model (DEM)
raster and then save the vector points to a vector layer. You can export
the vector points to any supported vector format or display them in
three-dimensions (3-D) over an image and use them for quality control
or editing.
Choosing between using vector points or contour lines is a matter of
personal preference. Vector points are easier to edit than contour lines,
because you have fewer points to analyse. Contour lines offer a more
intuitive view of the terrain, but you have more points to edit. For more
information about contour lines, see “Extracting Contour Lines from a
Digital Elevation Model” on page 96.
To extract a vector grid from a DEM:
1. On the OrthoEngine window in the Processing Step list, select 3-D
Operations.
2. Click
the Extract Vector Grid from DEM icon.
3. On the Extract Vector Grid window under Input DEM in the File
box, type the path where the DEM is found or click Browse to select
the file.
4. In the Channel list, click the DEM channel or click Select.
5. In the Failure Value box, type the failed pixel value.
• Full Image to extract a vector grid from the entire DEM.
• Window to extract a vector grid from a specific area. In the
Offset boxes type the pixel and line coordinates of the upper left
corner of the area and in the Size boxes type the number of pixels
and lines to specify its size.
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8. Under Output Grid in the File box, type the path where the vector
grid will be saved or click Browse to select the file.
9. Click Create new segment to add a new segment to the output file or
click Use existing segment to replace an existing vector segment.
10. In the Segment list, click the vector segment to be replaced or click
Select.
11. In the Grid Spacing box, type the number of pixels in the input DEM
that determines the space between two vector points.
12. Click Extract.
Extracting Contour Lines from a Digital
Elevation Model
You can extract vector contour lines from a digital elevation model
(DEM) raster and then save the contour lines to a vector layer. You can
export the contour lines to any supported vector format or display them
in three-dimensions over an image and use them for quality control or
editing.
Choosing between using contour lines or vector points is a matter of
personal preference. Vector points are easier to edit than contour lines
since you have fewer points to analyse. Contour lines offer a more
intuitive view of the terrain, but you have more points to edit. For more
information about vector points, see “Extracting Vector Points from a
Digital Elevation Model” on page 95.
To extract contours from a DEM:
3. On the Generate Contours window under Input DEM in the File
box, type the path where the DEM is found or click Browse to select
the file.
4. In the DEM Channel list, click the DEM channel or click Select.
5. In the Background Value box, type the background pixel value, if
necessary.
OrthoEngine may automatically extract the background pixel value
from the DEM, use the default values for the project, or consider all
the elevation values in the DEM as valid. It is very important to
specify the correct background pixel value or the contour lines will be
generated using all the values in the DEM, which may include large
negative values normally used as the background values.
6. In the Contour Interval box, type the span in DEM elevation units
that you want between the contour lines.
7. In the Field Name list, click a label for the attribute field where the
elevation values of the contour lines will be saved. If you choose the ZCoordinate label, the attribute field is omitted since all vector contour
lines are automatically assigned a z-coordinate corresponding to their
elevation values.
8. Under Input Window, click:
• Full Image to extract contours from the entire DEM.
• Window to extract contours from a specific area. In the Offset
boxes type the pixel and line coordinates of the upper left corner
of the area and in the Size boxes type the number of pixels and
lines to specify its size.
1. On the OrthoEngine window in the Processing Step list, select 3-D
Operations.
9. Under Output Contour in the File box, type the path where the
contours will be saved or click Browse to select a path.
2. Click
10. Click Generate Contours.
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the Generate Contours icon.
PCI Geomatics
CHAPTER
8
Correcting Your Images
Understanding Orthorectification
Figure 8.1: Using sensor geometry and a DEM to orthorectify imagery
Orthorectification is the process of using a rigorous math model and a
digital elevation model (DEM) to correct distortions in raw images as
shown in Figure 8.1. The rigorous math models, such as the Aerial
Photography or Satellite Orbital math models, provide a method to
calculate the position and orientation of the sensor at the time when the
image was taken. The DEM is a raster of terrain elevations. For more
information about math models and DEMs, see “Understanding the
Math Models” on page 5 and “Understanding Digital Elevation
Models” on page 63.
The quality of the orthorectified image is directly related to the quality
of the rigorous math model and the DEM. A poorly computed math
model, an inaccurate DEM, or a DEM incorrectly georeferenced to the
math model will cause errors in the orthorectified images.
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Chapter 8 - Correcting Your Images
Orthorectifying Your Images
Before you orthorectify your images, you must ensure that the Output
Pixel Spacing on the Set Projection window is set correctly. For more
information, see “Setting the Projection” on page 13. The Output
Pixel Spacing determines the resolution of the orthorectified images.
By default the channel type for your orthorectified images is the same
as your input channel. To change the output channel type, see “Setting
the Channel Type for Your Output Image” on page 129.
For more information about the status displayed in the Ortho Photo
Production window, see “Understanding the Status Descriptions” on
page 103.
To start processing your image:
1. On the OrthoEngine window in the Processing Step list, select
Ortho Generation.
2. Click
the Schedule ortho generation icon.
3. Under Available Photos, select the images that you want to process
and click the arrow button to move the images under Photos to
Process.
The images are processed in the order that they appear under Photos
to Process. If you have already orthorectified the image, Delete
existing file appears next to the image. When the image is
orthorectified, the previous version is replaced. If you have not
orthorectified the image previously, Create new file appears.
4. Under Photos to Process, select an image.
5. In Input Channels, click All to select all the image channels or click
Channels and type the channels that you want in the Channel box.
You can use a dash between the channel numbers to indicate a range
and a comma between individual channel numbers.
98
6. Repeat step 5 for the remaining images or select Apply input
channel selection to all files to use the same channel selection for
the remaining images.
7. You can delete the uncorrected image from the disk when the process is
complete. Select an image under Photos to Process, and select
Delete input file when done. Repeat for each image that you want to
delete after the image is processed.
8. Under Ortho Photo in the File box, you can type a new filename for
the orthorectified image or click Browse to select the file.
The default filename is “o_” followed by the raw image’s filename. If
you replace the default filename with the filename of an existing file
with matching georeferencing and resolution, the new orthorectified
image will replace the old. If the georeferencing and resolution of the
existing file do not match the new orthorectified image, you will have
to type a new filename.
9. The Upper Left and Lower Right values may be default values or
the extents from an existing orthorectified image. You can click
Recompute Ortho Bound to reset Upper Left and Lower Right to
the default values, which represent the computed footprint of the image
on the ground.
If the computed bounds appear too large or too small, it may indicate
errors in the math model or the DEM.
10. Under DEM, click Browse to select the DEM. On the Database File
Selection window, select the file and click Open. Select the database
channel containing the elevation. In the Background Elevation box,
type the value representing the “No Data” pixels in the DEM and click
Select.
If you do not know what the background value is, click DEM Info.
The DEM INFO window displays the three lowest and three highest
values. The background value is usually a dramatically different
value such as -150 or -999,999.
PCI Geomatics
Orthorectifying Your Images
The elevation reference in the DEM must match the elevation
reference of the imagery that you want to orthorectify. Most math
models are based on Mean Sea Level. However, two math models are
based on an ellipsoid: the RADARSAT Specific Model and the
Rational Functions model when it is used with the IKONOS GEO
Ortho Kit product. If you are using one of these models and your
DEM is not based on an ellipsoid, see “Converting the DEM Datum”
on page 126.
11. If you need to convert the values in the DEM, type the scale value in
the Elevation Scale box. For more information, see “Understanding
Elevation Scale and Offset” on page 100.
12. If you need to compensate for a difference in elevation, type the offset
value in the Elevation Offset box. For more information, see
“Understanding Elevation Scale and Offset” on page 100.
13. For Elevation Unit, click Meter or Feet to identify the unit that the
elevation numbers in your DEM represent.
14. If you want to use the same options set under DEM for all your images,
select Apply DEM options to all images.
Once you select Apply DEM options to all images, the DEM
options are set for all the images. Clearing the check mark will not
clear the DEM options set for any of the images. You will have to
reset the DEM options for each image separately.
15. In Working Cache, type the maximum amount of RAM that you
allocate for this process. The limit should not involve more than half
the RAM. Specifying more than half may significantly reduce
performance.
16. In Sampling Interval, type the interval between the pixels used to
process the image. Make sure that you set the interval correctly,
especially in rugged areas. Setting it too high will reduce the detail of
the terrain correction. For more information, see “Understanding
Sampling Interval” on page 102.
OrthoEngine User’s Guide
17. In the Resampling list, click the processing method of your choice.
For more information, see “Understanding the Resampling Options” on
page 104.
18. In Auto Clip Edge, type the percentage of the image’s outside edge
that you want to remove. You can use this option to remove unwanted
areas such as the data strip and fiducial marks from aerial photographs
or a dark perimeter or distortion along the edge of the image.
19. Depending on the Resampling option that you chose in step 17, one of
the following may become available:
• In Filter Size, type the number of pixels in width in the X box
and the number of pixels in length in the Y box to determine the
size of the frame used with the filter.
• In Gaussian SQ box, type the first value. In the 2 box, type the
second value to determine the size of the frame for the Gaussian
Filter.
• Click Browse to select the Kernel File.
20. Under Processing Start Time, click Start Now or Start at
(hh:mm) and set the time when you want the operation to begin
(within the next 24 hours).
21. Click Generate Orthos.
A progress monitor displays the status of the images being processed.
Click Cancel if you want to stop the process.
Tip
If you intend to automatically mosaic the processed images, you can click
Close instead of Generate Orthos. When you set up the Automatic
Mosaicking window, select Regenerate offline orthos, and
OrthoEngine will process the images and mosaic them in one step.
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elevation = Scale * (DEM pixel value + Offset)
Next step in your project . . .
You can continue with Mosaicking, see “Defining a Mosaic Area” on
page 112.
Continuing the same example, if you add the DEM pixel value to the
Elevation Offset (102 + 1,000) and multiply the result by the
Elevation Scale (1,102 * 0.1), then the DEM pixel value actually
represents an elevation value of 110.2.
Understanding Elevation Scale and Offset
The Elevation Scale is used to convert the pixel values in a digital
elevation model (DEM) into their correct elevation value. For
example: since an 8-bit channel can only contain integers between 0
and 255, you may have a DEM that was multiplied by 10 to maintain
the decimal precision of its elevation values. A DEM pixel may have a
value of 102, but the actual elevation that it represents is 10.2. To
convert the DEM pixel value from 102 to 10.2 you must multiply it by
0.1. Therefore, you type 0.1 in the Elevation Scale box to convert the
DEM pixels back to their true values.
The Elevation Offset is used to add a value to the pixel values in a
DEM to obtain their actual elevation value. Using the same example,
perhaps the DEM pixel with a value of 102 actually represents an
elevation value of 1,102. To store the elevation values in an 8-bit
channel, 1,000 was subtracted from all the pixel values when the DEM
was created. Therefore, you must type 1,000 in the Elevation Offset
box to restore the true values.
You can also use Elevation Offset to adjust the elevation reference of
a DEM. The elevations in a DEM can be calculated above Mean Sea
Level or an ellipsoid. The elevation reference in the DEM must match
the elevation reference of the imagery that you want to orthorectify. To
compensate for a discrepancy, you can type the difference between the
two elevation references in the Elevation Offset box. You can also
convert the DEM, see “Converting the DEM Datum” on page 126.
Tip
If you do not have a DEM, you can use the average elevation of an area to
orthorectify the image. However, this will not produce results as accurate as
using a DEM. Type the average elevation in the Elevation Offset box.
Understanding Geometric Correction
Simple math models, such as Polynomial, Thin Plate Spline, and
Rational Functions, use ground control points (GCPs) to calculate a
transformation that will warp the raw image to fit the ground
coordinates. The warping the raw image is known as geometric
correction (shown in Figure 8.2). For more information about simple
math models, see “Understanding the Math Models” on page 5 and
“Understanding the Solution for Simple Math Models” on page 56.
The quality of the geometrically corrected image is directly related to
the quality and number of the GCPs and the math model that you
choose. Selecting the wrong math model, collecting too few GCPs, or
inaccurately collecting the GCPs may result in a geometrically
corrected image that does not suit your needs.
The Elevation Scale and Elevation Offset can be used together to
convert the DEM pixel values to their actual elevation values. The
equation for the conversion is:
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Geometrically Correcting Your Images
Figure 8.2: The process of geometric correction
The images are processed in the order that they appear under Photos
to Process. If you have already corrected the image, Delete existing
file appears next to the image. When the image is processed, the
previous version is replaced. If you have not corrected the image
previously, Create new file appears.
4. Under Photos to Process, select an image.
5. In Input Channels, click All to select all the image channels or click
Channels and type the channels that you want in the Channel box.
You can use a dash between the channel numbers to indicate a range
and a comma between individual channel numbers.
6. Repeat step 5 for the remaining images or select Apply input
channel selection to all files to use the same channel selection for
the remaining images.
Geometrically Correcting Your Images
Before you process your images, you must make sure that the Output
Pixel Spacing on the Set Projection window is set correctly. For more
information, see “Setting the Projection” on page 13. The Output
Pixel Spacing determines the size of the corrected images.
For more information about the status displayed in the Geometric
Corrected Image Production window, see “Understanding the Status
Descriptions” on page 103.
To start processing your image:
1. On the OrthoEngine window in the Processing Step list, select
Geometric Correction.
2. Click
the Schedule Geometric Correction icon.
3. Under Available Photos, select the images that you want to process
and click the arrow button to move the images under Photos to
Process.
OrthoEngine User’s Guide
7. You can delete the uncorrected image from the disk when the process is
complete. Select an image under Photos to Process, and select
Delete input file when done. Repeat for each image that you want to
delete after the image is processed.
8. Under Corrected Image in the File box, you can type a new filename
for the corrected image or click Browse to select the file.
The default filename is “o” followed by the raw image’s filename. If
you replace the default filename with the filename of an existing file
with matching georeferencing and resolution, the newly corrected
image will replace the old. If the georeferencing and resolution of the
existing file do not match the newly corrected image, you will have to
type a new filename.
9. The Upper Left and Lower Right values may be default values or
the extents from an existing orthorectified image. You can click
Recompute Ortho Bound to reset Upper Left and Lower Right to
the default values.
10. In Working Cache, type the maximum amount of RAM that you
allocate for this process. The limit should not involve more than half
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the RAM. Specifying more than half may significantly reduce
performance.
11. In Sampling Interval, type the interval between the pixels used to
process the image. For more information, see “Understanding
Sampling Interval” on page 102.
12. In the Resampling list, click the processing method of your choice.
For more information, see “Understanding the Resampling Options” on
page 104.
13. Depending on the Resampling option that you chose, one of the
following may become available. These options are explained further
in “Understanding the Resampling Options” on page 104 under their
corresponding method.
• In Filter Size, type the number of pixels in width in the X box
and the number of pixels in length in the Y box to determine the
size of the frame used with the filter.
• In Gaussian SQ box, type the first value and in the 2 box type
the second value to determine the size of the frame for the
Gaussian Filter.
• Click Browse to select the Kernel File.
Understanding Sampling Interval
The Sampling Interval controls how the computations are performed
when an image is orthorectified or geometrically corrected.
When an image is corrected, OrthoEngine selects a pixel from the
output file, computes the elevation from the DEM (if available),
applies the math model to determine which pixel it corresponds to in
the raw image, and then transfers the data to the pixel in the output file.
The Sampling Interval determines how many output pixels are
computed following that method. A Sampling Interval of 1 means that
every output pixel is processed. However, processing every output
pixel can take a significant amount of time, and it may not be
necessary.
To speed up the process, you can increase the Sampling Interval, which
means that OrthoEngine computes the correction for some pixels and
interpolates those in between. For example, a Sampling Interval of 4
means that the correction for every fourth pixel is calculated and the
correction for the pixels in between are interpolated.
Hints for use with Orthorectification:
14. Under Processing Start Time, click Start Now or Start at
(hh:mm) and set the time when you want the operation to begin
(within the next 24 hours).
• When you have high-resolution images, such as aerial photographs, and
a high-resolution DEM, a lower Sampling Interval is recommended to
ensure that sharp changes in elevation are corrected during
orthorectification.
15. Click Correct Images.
• When the resolution of your images is higher than that of your DEM,
use a higher Sampling Interval. In this case, many output pixels will fall
within the boundaries of a single DEM pixel so using a higher interval
speeds up the process without compromising greatly on the output.
A progress monitor displays the status of the images being processed.
Click Cancel if you want to stop the process.
Tip
If you intend to automatically mosaic the processed images, you can click
Close instead of Generate Orthos. When you set up the Automatic
Mosaicking window, select Regenerate offline orthos, and
OrthoEngine will process the images and mosaic them in one step.
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• If you do not want to use all the detail in your DEM, use a higher
Sampling Interval.
• If you want to perform a trial run of the orthorectification to verify the
results, use a higher Sampling Interval. It will increase the processing
speed.
PCI Geomatics
Understanding the Status Descriptions
Hints for use with Geometric Correction:
When you are using simple math models, the main advantage of a
higher Sampling Interval is processing speed. Depending on the
complexity of the math model, a higher interval would likely have less
effect on the final accuracy than rigorous math models that use a DEM.
Understanding the Status Descriptions
Status descriptions for images under Available Photos (or
Available Images):
The status of the image determines which images can be processed.
• No model: You need to compute the math model before you process
the image, see “Performing the Bundle Adjustment for Rigorous Math
Models” on page 55 or “Understanding the Solution for Simple Math
Models” on page 56.
• Stale model: You have changed information in the project that may
have affected the math model. You should to recompute the math
model before you process the image, see “Performing the Bundle
Adjustment for Rigorous Math Models” on page 55.
• No Ortho: The model is up-to-date and a corrected version of the
image was not found. You can select the image and move it to Photos
to Process.
• Ortho stale: A corrected version of the image was found, but it does
not match the current math model. You can select the image and move
it to Photos to Process.
• Ortho done: A corrected version of the image was found, and it
matches the current math model. You do not need to reprocess the
image.
Status descriptions for images under Photos to Process (or
Images to Process):
• Delete Existing File: The previous version of the corrected image will
be replaced by the new one.
• Create New File: The corrected image will be saved on the disk.
Status descriptions for images under Uncorrected Photo (or
Uncorrected Image):
• No model computed: The math model was not computed and the
image cannot be processed, see “Collecting Control Points and
Computing the Math Models” on page 33.
• Project Changed (model stale): The math model may be out-of-date.
To recompute the math model, see “Performing the Bundle Adjustment
for Rigorous Math Models” on page 55.
• Model up-to-date: The math model is current and can be used to
process the image.
Status descriptions for images under Ortho Photo (or
Corrected Image):
• No ortho generated: A corrected version of the image was not found
on the disk.
• Model updated since last ortho generated: A corrected version of
the image was found on the disk, but it does not match the current math
model.
• Ortho matches computed model: A previous version of the
corrected image was found on the disk, and the same math model was
used for both.
• File exists. Will DELETE existing file: The previous version of the
corrected image will be replaced by the new one.
• Currently Off-line. New file will be created: The image was
previously processed, but the file was not found.
• New file will be created: The corrected image will be saved on the
disk.
The status displayed beside the image explains what happens after you
process the images.
OrthoEngine User’s Guide
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Troubleshooting Your Orthorectified
Images
Features that would be straight in a planimetric map, such as roads,
power lines, edges of buildings, and edges of lots, should also appear
straight in an orthorectified image. If they do not, then you may have
errors in your digital elevation model (DEM) or math model solution.
Re-verify the DEM and the math model solution.
If the file for the orthorectified image is too large or too
small, it may indicate that:
• The DEM area does not cover the image area
• The DEM is not in the same projection as the image
• The Background Value of the DEM is incorrect
• The math model’s elevation values are incorrect
• The focal length of camera is incorrect
• The image is not from the demo data sets, and you are working in demo
mode (unlicensed)
• The DEM file is not accessible (offline)
• The filename of the orthorectified image is missing
• The math model is not computed
• The orthorectified image already exists, but its georeferencing or
resolution is incorrect.
Understanding the Resampling Options
Resampling extracts and interpolates the gray levels from the original
pixel locations to corrected locations.
These methods are available:
• “Nearest (Nearest Neighbor Interpolation)” on page 105
• “Bilinear (Bilinear Interpolation)” on page 105
If the orthorectified image appears smeared, it could
indicate that:
• “Cubic (Cubic Convolution)” on page 105
• The DEM is misaligned with the math model of the image
• “Average Filter” on page 106
• The DEM does not have a sufficient resolution to orthorectify the
image. For example, cliffs and buildings can appear smeared if the
DEM is too coarse to precisely represent the edge of the cliff or the
building.
• “Median Filter” on page 106
If overlapping orthorectified images do not align, it could
indicate that:
The following filters are only available for radar images:
• The math model contains errors, which means that you need to edit the
model or add more GCPs and tie points.
• “Radar Enhanced Frost Filter” on page 108
• The DEM contains errors or contains insufficient detail to correctly
orthorectify the images.
• “Radar Enhanced Lee Filter” on page 110
If OrthoEngine does not generate the orthorectified image:
• The image to be processed is not accessible (offline).
104
• “Sin (8 Pt and 16 Pt SinX/X)” on page 105
• “Gaussian Filter” on page 106
• “User Defined Filter” on page 106
• “Radar Gamma Filter” on page 107
• “Radar Kuan Filter” on page 109
For Reference
The implementation of the speckle filters were based on the following
papers, and especially the review paper by Shi and Fung.
PCI Geomatics
Understanding the Resampling Options
Jong-Sen Lee, “Digital Image Enhancement and Noise Filtering by Use of
Local Statistics”, IEEE Transactions on Pattern Analysis and Machine
Intelligence, Vol. PAM 1-2, No. 2, March, 1980.
J.S. Lee, “Refined Filtering of Image Noise Using Local Statistics”
Computer Graphic and Image Processing 15, p. 380 to 389 (1981)
D.T. Kuan, A.A. Sawchuk, T.C. Strand, and P. Chavel, “Adaptive
restoration of images with speckle,” IEEE Trans. ASSP., Vol. 35, no. 3, pp.
373 to 383, March 1987.
A. Lopes, R. Touzi and E. Nezry, “Adaptive speckle filters and Scene
heterogeneity”, IEEE Transaction on Geoscience and Remote Sensing,
Vol. 28, No. 6, pp. 992 to 1000, Nov. 1990.
V.S. Frost, J.A. Stiles, K.S. Shanmugan, and J.C. Holtzman, “A model for
radar images and its application to adaptive digital filtering of multiplicative
noise,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 4, no.
2, pp. 157 to 166, March 1982.
A. Lopes, E. Nezry, R. Touzi, and H. Laur, “Structure detection and
statistical adaptive speckle filtering in SAR images”, International Journal of
Remote Sensing, Vol. 14, No. 9, pp. 1735 to 1758, 1993.
A. Lopes, R. Touzi and E. Nezry, “Adaptive speckle filters and Scene
heterogeneity”, IEEE Transaction on Geoscience and Remote Sensing,
Vol. 28, No. 6, pp. 992 to 1000, Nov. 1990.
Zhenghao Shi and Ko B. Fung, 1994, “A Comparison of Digital Speckle
Filters”, Proceedings of IGARSS 94, August 8-12, 1994.
Nearest (Nearest Neighbor Interpolation)
The Nearest Neighbor Interpolation resampling option identifies the
gray level of the pixel closest to the specified input coordinates and
assigns that value to the output coordinates. Although this method is
considered the most efficient in terms of computation time, it
introduces small errors in the output image. The output image may be
OrthoEngine User’s Guide
offset spatially by up to half a pixel, which may cause the image to
have a jagged appearance.
Bilinear (Bilinear Interpolation)
The Bilinear Interpolation resampling option determines the gray
level from the weighted average of the four closest pixels to the
specified input coordinates and assigns that value to the output
coordinates. This method generates an image with a smoother
appearance than Nearest Neighbor Interpolation, but the gray level
values are altered in the process, which results in blurring or loss of
image resolution.
Cubic (Cubic Convolution)
The Cubic Convolution resampling option determines the gray level
from the weighted average of the 16 closest pixels to the specified
input coordinates and assigns that value to the output coordinates. The
resulting image is slightly sharper than one produced by Bilinear
Interpolation, and it does not have the disjointed appearance produced
by Nearest Neighbor Interpolation.
Sin (8 Pt and 16 Pt SinX/X)
The 8 Pt SinX/X resampling option determines the gray level from the
weighted average of the 64 closest pixels to the specified input
coordinates and assigns the value to the output coordinates.
The 16 Pt SinX/X resampling option determines the gray level from
the weighted average of the 256 closest pixels to the specified input
coordinates and assigns the value to the output coordinates.
The resulting image from using either of these methods is sharper than
one produced by Bilinear Interpolation, and it does not have the
disjointed appearance produced by Nearest Neighbor Interpolation.
However, since the gray level values are altered by these methods,
image classification processes should be performed before the
interpolation.
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Average Filter
The Average Filter resampling option determines the gray level from
the mean of all pixels in a square or rectangular frame surrounding the
input coordinates and assigns the value to the output coordinates.
The mean is determined by calculating the sum of all pixels in the
frame and then dividing by the number of pixels in the frame. To filter
pixels located near the edges of the image, edge pixel values are
replicated to produce sufficient data. This method smooths the
appearance of the image.
You control the size of the frame with the Filter Size option by typing
the number of pixels in width in the X box and the number of pixels in
length in the Y box.
Median Filter
The Median Filter resampling option determines the gray level from
the median value of all pixels in a square or rectangular frame
surrounding the input coordinates and assigns the value to the output
coordinates.
The median is obtained by ranking the gray levels according to
brightness and determining the middle value. To filter pixels located
near the edges of the image, edge pixel values are replicated to produce
sufficient data. This method smooths the appearance of the image.
You control the size of the frame with the Filter Size option by typing
the number of pixels in width in the X box and the number of pixels in
length in the Y box.
Gaussian Filter
The Gaussian Filter resampling option determines the gray level from
the weighted sum of all the pixels in a square or rectangular frame
surrounding the input coordinates and assigns the value to the output
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coordinates. To filter pixels located near the edges of the image, edge
pixel values are replicated to produce sufficient data.
The filter weights are computed using a Gaussian function:
G(i,j) = exp(-((i-u)**2 + (j-v)**2)/(2 * Gaussian
SQ))
where (i,j) is a pixel within the frame, and Gaussian SQ is the square
of the Gaussian distribution deviation.
You control the size of the frame by typing a value between 1.0 and
32.0 in each of the Gaussian SQ boxes. The filter weights W(i,j) are
the normalized values of G(i,j) in the frame. The sum of all the weights
is 1. The gray level of a filtered pixel is the sum of W(i,j) * V(i,j) over
all pixels in the frame, where V(i,j) is the original value at location (i,j).
If only the first Gaussian SQ value is specified, then the Gaussian Filter
is a low-pass filter with a square frame of 2*SQ + 1. As a result, the
image will be blurred.
If the second Gaussian SQ value is specified, then the Gaussian Filter
is a band-pass filter with a frame of 2n*1, where “n” is the larger of the
two SQ values. The resulting image is the difference of the image
produced with the second SQ subtracted from the image produced with
the first SQ. As a result, it will detect sudden intensity changes in the
image.
User Defined Filter
The User Defined Filter resampling option determines the gray level
from the weighted average of all the pixels in a square or rectangular
frame surrounding the input coordinates and assigns the value to the
output coordinates.
The weight applied to each pixel in the frame is defined in a Kernel
File that you create with a text editor such as Notepad. Click Browse
to select the Kernel File.
PCI Geomatics
Understanding the Resampling Options
For example, if you wanted to create a 3-by-3 Kernel File, you could
define it as this:
-1
1
1
-1
3
-1
0
1
-1
The Kernel File moves over the image. Each pixel that falls within the
frame is multiplied by the corresponding number in the filter, and then
summed to produce the output value.
Im = mean value of intensity within the frame
S = standard deviation of intensity within the frame
Ic = center pixel in the frame
A = (1+Cu^2)/(Ci^2-Cu^2)
B = A-Number of Looks-1
D = Im*Im*B*B + 4*A*Number of Looks*Im*Ic
The Number of Looks and the Image Format of the radar image are
usually recorded on the CD jacket or magnetic tape label or in the
format specifications provided by the data vendor.
Radar Gamma Filter
Filter Size:
The Radar Gamma Filter resampling option determines the gray
level for each pixel by computing a set of weighted values in a square
frame surrounding the pixel. To filter pixels located near the edges of
the image, edge pixel values are replicated to produce sufficient data.
The frame must be square with its width and length in odd numbers.
You control the size of the frame with the Filter Size option by typing
the number of pixels (width) in the X box and the number of lines
(length) in the Y box. Different filter sizes greatly affect the quality of
the processed images. If the filter is too small, the noise filtering
algorithm is not effective. If the filter is too large, subtle details of the
image are lost in the filtering process. The minimum size for the frame
is 3-by-3 pixels. A 7-by-7 frame usually gives the best results.
This filter is used primarily to suppress speckle. It smooths image data,
without removing edges or sharp features in the images. You can use
this filter for a wide range of Gamma-distributed images, such as those
containing forested areas, agricultural lands, and oceans. The filter also
preserves the observed pixel value for non-Gamma-distributed images.
The Gamma filter minimizes the loss of texture information since it
uses the statistical properties of the underlying image.
Assuming a Gamma-distributed image, the resulting gray-level value
(R) for the smoothed pixel is:
R = Im for Ci <= Cu
R = Rf for Cu < Ci < Cmax
R = Ic for Ci >= Cmax
where:
Rf = (B*Im + SQRT(D))/(2*A)
Ci = S / Im
Cu = SQRT(1/Number of Looks)
Cmax = SQRT(2)*Cu
OrthoEngine User’s Guide
Image Format:
The radar images are supplied in one of two Image Formats: Power or
Amplitude. Power is the sum of the squares of the real and imaginary
values of the complex pixel values in the radar image. Amplitude is the
square root of Power. Most radar images are supplied in the Amplitude
format to preserve the values. You identify the format used with your
images in the Image Format list.
Number of Looks:
You use the Number of Looks to estimate noise variance and to control
the amount of smoothing applied to the image. In theory, the correct
value for the Number of Looks should be the effective number of looks
of the radar image, or close to the actual number, but it may be different
if the image was resampled. Using a smaller value for the Number of
Looks leads to more smoothing, and a larger value preserves more
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image features. In the No. of Looks list, select the Number of Looks
that you want to apply to the image.
T = the absolute value of the pixel distance from the center pixel to its
neighbors in the frame
Radar Enhanced Frost Filter
The Damping Factor specifies the extent of the damping effect of
filtering. OrthoEngine uses a default value of 1 since it is sufficient for
most SAR images.
The Radar Enhanced Frost (Radar Enh_Frost Filter) resampling
option determines the gray level for each pixel by computing the
weighted sum of the center pixel value, the mean value, and the
variance calculated in a circular frame surrounding the pixel. To filter
pixels located near the edges of the image, edge pixel values are
replicated to produce sufficient data.
This filter is used primarily to suppress speckle. It smooths image data
without removing edges or sharp features in the images while
minimizing the loss of radiometric and textural information. In
homogeneous areas, speckles are removed using a low-pass filter. In
areas containing isolated point targets, the filter preserves the observed
value. In heterogeneous areas, speckles are reduced by convolving the
image with a circular kernel. The resulting gray-level value (R) for the
smoothed pixel is:
R = Im for Ci <= Cu
R = Rf for Cu < Ci < Cmax
R = Ic for Ci >= Cmax
Where Rf is the result of convolving the image with a circularly
symmetric filter whose weighting values (M) for each pixel is:
M = exp(- A * T)
where:
A = Damping Factor * (Ci-Cu)/(Cmax-Ci)
Ci = S / Im
Cu = SQRT(1/Number of Looks)
Cmax = SQRT(1+2/Number of Looks)
Im = mean value of intensity within the frame
S = standard deviation of intensity within the frame
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The resulting gray-level value (Rf) for the smoothed pixel is:
Rf = (P1*M1 + P2*M2 + ... + Pn*Mn) / (M1 + M2 + ...
+ Mn)
where:
P1 .. Pn are gray levels of each pixel in frame
M1 .. Mn are weights (as defined above) for each pixel
The Number of Looks and the Image Format of the radar image are
usually recorded on the CD jacket or magnetic tape label or in the
format specifications provided by the data vendor.
Filter Size:
The frame is circular with its width and length in odd numbers. You
control the size of the frame with the Filter Size option by typing the
number of pixels (width) in the X box and the number of lines (length)
in the Y box. Different filter sizes greatly affect the quality of the
processed images. If the filter is too small, the noise filtering algorithm
is not effective. If the filter is too large, subtle details of the image are
lost in the filtering process. The minimum size for the frame is 3-by-3
pixels. A 7-by-7 frame usually gives the best results.
Image Format:
The radar images are supplied in one of two Image Formats: Power or
Amplitude. Power is the sum of the squares of the real and imaginary
values of the complex pixel values in the radar image. Amplitude is the
square root of Power. Most radar images are supplied in the Amplitude
PCI Geomatics
Understanding the Resampling Options
format to preserve the values. You identify the format used with your
images in the Image Format list.
Im = mean value of intensity within the frame
S = standard deviation of intensity within the frame
Number of Looks:
The Number of Looks and the Image Format of the radar image are
usually recorded on the CD jacket or magnetic tape label or in the
format specifications provided by the data vendor.
You use the Number of Looks to estimate noise variance and to control
the amount of smoothing applied to the image. In theory, the correct
value for the Number of Looks should be the effective number of looks
of the radar image, or close to the actual number, but it may be different
if the image was resampled. Using a smaller value for the Number of
Looks leads to more smoothing, and a larger value preserves more
image features. In the No. of Looks list, select the Number of Looks
that you want to apply to the image.
Radar Kuan Filter
The Radar Kuan resampling option determines the gray level for each
pixel by replacing the center pixel with a weighted average of the
central pixel and the mean of the values in a square frame surrounding
the pixel. To filter pixels located near the edges of the image, edge
pixel values are replicated to produce sufficient data.
This filter is used primarily to suppress speckle. It smooths image data
without removing edges or sharp features in the images while
minimizing the loss of radiometric and textural information. The Kuan
filter first transforms the multiplicative noise model into a signaldependent additive noise model. Then the minimum mean square error
criterion is applied to the model. The resulting gray-level value (R) for
the smoothed pixel is:
R = Ic * W + Im * (1 - W)
where:
W = (1 - Cu^2/Ci^2)/(1+Cu^2)
Cu = SQRT(1/Number of Looks)
Ci = S / Im
Ic = center pixel in the frame
OrthoEngine User’s Guide
Filter Size:
The frame must be square with its width and length in odd numbers.
You control the size of the frame with the Filter Size option by typing
the number of pixels (width) in the X box and the number of lines
(length) in the Y box. Different filter sizes greatly affect the quality of
the processed images. If the filter is too small, the noise filtering
algorithm is not effective. If the filter is too large, subtle details of the
image are lost in the filtering process. The minimum size for the frame
is 3-by-3 pixels. A 7-by-7 frame usually gives the best results.
Image Format:
The radar images are supplied in one of two Image Formats: Power or
Amplitude. Power is the sum of the squares of the real and imaginary
values of the complex pixel values in the radar image. Amplitude is the
square root of Power. Most radar images are supplied in the Amplitude
format to preserve the values. You identify the format used with your
images in the Image Format list.
Number of Looks:
You use the Number of Looks to estimate noise variance and to control
the amount of smoothing applied to the image. In theory, the correct
value for the Number of Looks should be the effective number of looks
of the radar image, or close to the actual number, but it may be different
if the image was resampled. Using a smaller value for the Number of
Looks leads to more smoothing, and a larger value preserves more
image features. In the No. of Looks list, select the Number of Looks
that you want to apply to the image.
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Radar Enhanced Lee Filter
The Radar Enhanced Lee (Radar Enh_Lee Filter) resampling option
determines the gray level for each pixel by computing the weighted
sum of the center pixel value, the mean value, and the variance
calculated in a square frame surrounding the pixel. To filter pixels
located near the edges of the image, edge pixel values are replicated to
produce sufficient data.
This filter is used primarily to suppress speckle. It smooths image data
without removing edges or sharp features in the images while
minimizing the loss of radiometric and textural information. In
homogeneous areas speckles are removed using a low-pass filter. In
heterogeneous areas, speckles are reduced while preserving the
texture. In areas containing isolated point targets, the filter preserves
the observed value. The resulting gray-level value (R) for the smoothed
pixel is:
R = Im for Ci <= Cu
R = Im * W + Ic * (1-W) for Cu < Ci < Cmax
R = Ic for Ci >= Cmax
where:
W = exp (-Damping Factor (Ci-Cu)/(Cmax - Ci))
Cu = SQRT(1/Number of Looks)
Ci = S / Im
Cmax = SQRT(1+2/Number of Looks)
Ic = center pixel in the frame
Im = mean value of intensity within the frame
S = standard deviation of intensity within the frame
The Damping Factor specifies the extent of the damping effect of
filtering. OrthoEngine uses a default value of 1 since it is sufficient for
most SAR images.
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The Number of Looks and the Image Format of the radar image are
usually recorded on the CD jacket or magnetic tape label or in the
format specifications provided by the data vendor.
Filter Size:
The frame must be square with its width and length in odd numbers.
You control the size of the frame with the Filter Size option by typing
the number of pixels (width) in the X box and the number of lines
(length) in the Y box. Different filter sizes greatly affect the quality of
the processed images. If the filter is too small, the noise filtering
algorithm is not effective. If the filter is too large, subtle details of the
image are lost in the filtering process. The minimum size for the frame
is 3-by-3 pixels. A 7-by-7 frame usually gives the best results.
Image Format:
The radar images are supplied in one of two Image Formats: Power or
Amplitude. Power is the sum of the squares of the real and imaginary
values of the complex pixel values in the radar image. Amplitude is the
square root of Power. Most radar images are supplied in the Amplitude
format to preserve the values. You identify the format used with your
images in the Image Format list.
Number of Looks:
You use the Number of Looks to estimate noise variance and to control
the amount of smoothing applied to the image. In theory, the correct
value for the Number of Looks should be the effective number of looks
of the radar image, or close to the actual number, but it may be different
if the image was resampled. Using a smaller value for the Number of
Looks leads to more smoothing, and a larger value preserves more
image features. In the No. of Looks list, select the Number of Looks
that you want to apply to the image.
PCI Geomatics
CHAPTER
9
Mosaicking Your Images
Understanding Mosaicking
Figure 9.1: Mosaicking
Mosaicking is joining together several overlapping images to form a
uniform image as shown in Figure 9.1. Basically, it is similar to
creating a jigsaw puzzle with your images, and then making the joints
disappear.
For the mosaic to look like one image instead of a collage of images, it
is important that the images fit well together. You will achieve better
results if you orthorectify your images. Using a rigorous math model
ensures the best fit not only for the individual images, but for all the
images united as a whole. For more information, see “Starting your
Project and Selecting a Math Model” on page 5 and “Correcting Your
Images” on page 97.
To achieve that seamless look in the mosaic, place the joints, called
cutlines, where they will be the least noticeable and select images or
portions of images that are not radically different in color.
To begin a Mosaic Only project with a set of existing corrected
images, see “Starting a Project to Mosaic Existing Georeferenced
Images” on page 12.
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Defining a Mosaic Area
The Mosaic Area determines the extents of the mosaic file. The images
are added to the Mosaic Area like pieces of a puzzle. On the Define
Mosaic Area window, the footprints of the images in your project are
displayed as they overlap. The crosshairs represent the principal point
of each image. Click one of the crosshairs to reveal the footprint of an
individual image. You can drag a frame around the area that you want
to include in the mosaic or select an existing mosaic file. The
background value of the Mosaic Area is zero by default.
For more information about Mosaicking, see “Understanding
Mosaicking” on page 111.
To drag a frame to define the Mosaic Area:
1. On the OrthoEngine window in the Processing Step list, select
Mosaic.
2. Click
the Define mosaic area icon.
3. On the Define Mosaic Area window, press the SHIFT key and drag a
frame over the area that you want. To clear the frame, click Define
New Mosaic Area. To change the coordinates under Mosaic
Extents, see “Editing the Mosaic Extents” on page 113.
4. Under Mosaic File Information in the Channels list, click:
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• 16 Bit Unsigned to set the range of pixel values in the images
from 0 to 65,535. The range of values is the same as explained for
16 Bit Signed, however, Unsigned means it uses only positive
integers, therefore, the range is set from 0 to 65,535.
• 32 Bit Real to set the range of pixel values that includes decimals
and positive and negative values. The term 32 Bit Real is a range
of real numbers that is expressed as -1.2E-38 to +3.4E+38. This
option takes the most amount of disk space.
5. If you selected None (Mosaic Only) when you set up the project,
Input Image Background Value becomes available. Type the
background value of the images that you want to mosaic or click to
clear the check mark if the background value is zero. For more
information, see “Mosaicking Images with a Background Value Other
Than Zero” on page 113.
6. Click Create Mosaic File.
7. Click Close.
To select a previously defined mosaic area:
1. On the OrthoEngine window in the Processing Step list, select
Mosaic.
2. Click
the Define mosaic area icon.
• 8 Bit Unsigned to set the range of pixel values in the images
from 0 to 255. The term 8 Bit determines the range of values by
calculating 2 to the eighth power (28), which equals 256.
Unsigned means it uses only positive integers, therefore, the range
is set from 0 to 255. This option takes the least amount of disk
space.
3. Click Select Existing Mosaic File.
• 16 Bit Signed to set the range of pixel values in the images from
-32,767 to +32,767. The term 16 Bit determines the range of
values by calculating 2 to the sixteenth power (216), which equals
65,536. Signed means it uses both positive and negative integers,
therefore, the range is set from -32,767 to +32,767.
Next step in your project . . .
See “Mosaicking Images Automatically” on page 113 or “Mosaicking
Images Manually” on page 115.
4. Select a mosaic file.
5. Click Close.
PCI Geomatics
Mosaicking Images Automatically
Editing the Mosaic Extents
After dragging the frame to determine the mosaic area, the dimensions
of the frame are displayed under Mosaic Extents. To edit the
dimensions, you can:
• place the pointer over the side or corner of the frame and move it to
change its size and shape.
• click UL & LR Corner in the list under Mosaic Extents, and then
type new x and y coordinates for the upper left and lower right corners
of the frame.
• click UL & Size in the list under Mosaic Extents. Type new x and y
coordinates for the upper left corner of the frame. Type the number of
pixels in X Size and the number of lines in Y Size to specify the size of
the frame.
• click Center & Size in the list under Mosaic Extents. Type new x and
y coordinates for the center of the frame. Type the number of pixels in
X Size and the number of lines in Y Size to specify the size of the
frame.
However, once the Mosaic file is created, you cannot move the frame
or edit the Mosaic Extents.
Mosaicking Images with a Background Value Other
Than Zero
OrthoEngine uses a background value of zero for orthorectified or
geometrically corrected images so the Mosaic Area also has a
background value of zero by default. However, images orthorectified
or geometrically corrected outside of OrthoEngine may have a
background value other than zero.
To mosaic images that were not processed in OrthoEngine, you need to
identify the background value of those images. After you identify the
background value, OrthoEngine will not include that value when the
images are added to the mosaic file. Therefore, the final mosaic will
only contain valid data from the images.
OrthoEngine User’s Guide
You identify the background value on the Define Mosaic Area window
in the Input Image Background Value box, see step 5 in “Defining a
Mosaic Area” on page 112.
Mosaicking Images Automatically
Although you can create your mosaic one image at a time by using
Manual Mosaicking (see “Mosaicking Images Manually” on
page 115), most of the time you will use Automatic Mosaicking to do
the bulk of the work, and you will use Manual Mosaicking to edit
portions of the mosaic file. Some projects may require more editing
than others, such as those containing large bodies of water or urban
areas with buildings leaning in different directions.
In addition to reducing your work load, Automatic Mosaicking will
often produce a more seamless look than if you had attempted to create
the mosaic by hand.
To automatically mosaic your images:
Before you attempt Automatic Mosaicking, you must define a mosaic
area, see “Defining a Mosaic Area” on page 112.
1. On the OrthoEngine window in the Processing Step list, select
Mosaic.
2. Click
the Automatic mosaicking icon.
3. In the Automatic Mosaicking window, click in the Use column to
select or clear the images. The images with check marks in the Use
column will be mosaicked. You can also use the Orthos in Mosaic
buttons to select or clear the images, click:
• All to select all the available images. Gray check marks indicate
images outside the defined mosaic area.
• None to clear all the images selected in the Use column.
• All in Mosaic to select only the images that appear in the region
that you set in Define Mosaic Area.
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4. Normalization is used to even out the maximum and minimum
effects in tone to achieve a more pleasing mosaic. You can set the
feature differently for each image by clicking the corresponding arrow
beside the Normalization column or you can set it for all the images
by selecting the feature in the Normalization list and clicking Apply
to All. Select:
• None to leave the images as is.
• Hot Spot to remove hot spots from the image. A hot spot is a
common distortion that results from solar reflections. Hot Spot
normalizes the brightness over the image, but it does not remove
spot reflections from lakes, cars, and buildings.
• Across Image 1st Order to correct the gradual change in
brightness from one side of the image to the other. OrthoEngine
computes a linear equation for the column averages of the image
to compensate for the consistent across-track gradation in tone.
Recommended for ScanSAR and other imagery.
• Across Image 2nd Order to correct the gradual change from
dark to bright to dark or vice versa across the image, also known
as an “antenna pattern”. OrthoEngine computes a quadratic
equation for the column averages of the image to compensate for
the varying across-track gradation in tone. Recommended for
ScanSAR and other imagery.
• Across Image 3rd Order to correct gradual bright and dark
patterns from one side of the image to the other. OrthoEngine
computes a cubic equation for the column averages of the image
to compensate for the inconsistent gradation in tone.
Recommended for ScanSAR and other imagery.
5. You can select Regenerate offline orthos to regenerate
orthorectified images with a Stale or Offline status. Projects with
“None (Mosaic Only)” as the math model do not have this option.
OrthoEngine can orthorectify the images and mosaic them in one
step, see the tip on page 99.
6. Automatic color balancing applies tonal and contrast adjustments over
the mosaic. For more information, see “Understanding Color
Balancing” on page 117. In the Color Balance list, select a method:
• None if you do not want to apply color balancing.
• Entire Image to use the histogram of each entire image to
compute the color balancing. This method is recommended for
images with low overlap or for images with systematic effects
such as when images are bright at the top and dark at the bottom.
• Overlap Area to use only the pixels where the images overlap to
compute the color balancing This method is recommended for
most images.
7. Cutlines are drawn in areas where the seams are the least visible based
on the radiometric values of the overlapping images. For more
information, see “Understanding Cutlines” on page 117. In Cutline
Selection Method, select:
• Min Difference to place the cutline in areas where there is the
least amount of difference in gray values between the images.
• Min Relative Difference to place the cutline in areas where
there is the least amount of difference in gradient values between
the images.
• Edge features to use a combination of Min Difference and Min
Relative Difference to determine the optimum location for the
cutline.
• Use Entire Image to mosaic images that do not overlap.
OrthoEngine uses the four corner coordinates of the images as the
cutlines to avoid gaps between the images.
8. Under Processing Start Time, click Start Now or Start at
(hh:mm) and set the time when you want the operation to begin
(within the next 24 hours).
9. In the box under Directory for Temporary Files, type the path for
the temporary working files or click Browse to select a location. The
temporary files are deleted when the mosaic is complete.
10. Click Generate Mosaic.
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PCI Geomatics
Mosaicking Images Manually
Tip
To view the mosaic, click File from the main menu and select Image View.
3. On the Manual Mosaicking window, click Select Image to Add and
double-click the crosshairs of the image that you want or click an
image from under Project Image Files.
Image already included in the Mosaic Area appear in red. Selected
images appear in cyan. Overlapping areas appear in gray.
Mosaicking Images Manually
You can create your mosaic one image at a time or you can use
Automatic Mosaicking to do the bulk of the work, see “Mosaicking
Images Automatically” on page 113. You can use Manual Mosaicking
to edit the cutlines in an automatically mosaicked project or to replace
unsatisfactory areas in the mosaic. For each image that you want to
include in the mosaic file, you must complete four steps in sequence.
If you are adding the first image to the file, you can skip Collect
Cutline and Color Balancing. Follow the steps to add the image to the
mosaic, and then return to Select Image to Add to work on the
remaining images.
4. Select Show Mosaic Preview if you want to view the contents of the
Mosaic Area.
Follow the procedures in:
1. Adding an Image to the Mosaic
Next step in your project . . .
Continue with steps in “Collecting the Cutline” on page 115.
2. Collecting the Cutline
3. Adjusting the Color Balance
4. Adding the Image to the Mosaic Area
Collecting the Cutline
For more information about cutlines, see “Understanding Cutlines” on
page 117.
Tip
Overviews quicken the display of your images, but they add processing
time when they are created.To speed up mosaicking, disable Build
Overview. See “Understanding When To Build Overviews” on page 129.
Continuing the steps from “Adding an Image to the Mosaic”
on page 115:
Adding an Image to the Mosaic
2. At an appropriate zoom level where you can see the detail in the image,
position the cursor where you want to begin collecting the cutline.
Under Cutline Information, click Add.
To mosaic your images:
1. On the OrthoEngine window in the Processing Step list, select
Mosaic.
2. Click
1. Under Mosaicking Steps, click Collect Cutline.
For more information about how to see the details in the image more
clearly, see “Changing the Layout in the Manual Mosaicking
Window” on page 118.
the Manual mosaicking icon.
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Chapter 9 - Mosaicking Your Images
3. Click in the viewer to outline a polygon around the area that you want
in the Mosaic Area. Draw the cutline in the areas that appear in gray or
cyan, and include some overlap between the images. Click Add when
you are finished the cutline.
3. Brightness is available for projects using 8-bit channels. It controls
the range of values available in the lookup table computed from the
match areas. In the Dark End and Light End boxes type or select the
values to determine the lower and upper limits of the range.
4. Under Cutline Information, the table displays the vertices collected
to form the cutline. To edit the cutline, select a vertex in the viewer or
in the table, click Move, Delete, or Insert, perform the edit, and then
click the same button again to end the edit.
4. Click Save Working LUT (for Mosaic Areas using 8-bit channels) or
Save Working State to save the lookup table with the image.
5. Click Finish.
6. In the Blend Width list, type or select the number of pixels on either
side of the cutline used to blend the seam. A Blend Width of three to
five pixels is recommended. You can see the results of the blend in the
Mosaic Preview window. For more information, see “Blending the
Seams” on page 117.
Next step in your project . . .
Continue with steps in “Adjusting the Color Balance” on page 116.
Note
If you reopen Color Balancing, the lookup table saved with the image is
not shown automatically. Click Show Saved LUT (for Mosaic Areas using
8-bit channels) or Show Saved State to display the lookup table and the
match areas that were saved with the image. The saved lookup table
cannot be edited. If you select new match areas and click Save Working
LUT or Save Working State, the previous lookup table is replaced.
Next step in your project . . .
Continue with steps in “Adding the Image to the Mosaic Area” on page 116.
Adding the Image to the Mosaic Area
Adjusting the Color Balance
For more information about color balancing, see “Understanding Color
Balancing” on page 117.
Continuing the steps from “Adjusting the Color Balance” on
page 116:
1. Under Mosaicking Steps, click Add Image to Mosaic.
Continuing the steps from “Collecting the Cutline” on
page 115:
1. Under Mosaicking Steps, click Color Balancing.
2. Click New Area and drag a rectangle in the overlap area to select a
match area. Repeat as many times as necessary. Select Show Mosaic
Preview to see how each match area affects the image that you are
adding to the mosaic.
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2. Click Add Image to Mosaic File to complete the mosaicking
process.
The selected portion of the image is added to the Mosaic Area.
3. Return to step 3 of “Adding an Image to the Mosaic” on page 115 and
repeat the steps for each image you want in the mosaic.
PCI Geomatics
Understanding Cutlines
Blending the Seams
Blending reduces the appearance of seams by mixing the pixels values
on either side of the cutline to achieve a gradual transition between the
images.
In Automatic Mosaicking OrthoEngine blends the seams
automatically. In Manual Mosaicking the Blend Width determines the
number of pixels on either side of the cutline that are used to blend the
seam. However, in areas containing bright or significantly different
features, setting the Blend Width too high may cause “ghosting” or
doubling of the features.
Understanding Cutlines
When you create a mosaic, you want to crop the images so the best
portions of the images are seamlessly joined together. A cutline is a
polygon that outlines the portion of an image that will be used in the
mosaic.
As the cropped images are added to the Mosaic Area, the data in
overlapping areas is covered by the most recent addition. Areas where
several images overlap provide you with the more opportunities to find
the best location for the cutlines. When you save the project, the
cutlines are saved with their corresponding images.
To make the seams between images less visible, select features that are
consistent in tone and texture, low to the ground, uniform in
appearance, and conspicuous such as roadways and river edges.
Features that display clear boundaries provide a natural camouflage for
the seam.
Avoid:
• Buildings or man-made features since they may lean in different
directions in the imagery.
• Large bodies of water, because waves may look different in different
images, and water tends to have different color in different images.
OrthoEngine User’s Guide
• Areas that are significantly different in color and texture, such as forests
and cultivated land, since they may look different from image to image.
Understanding Color Balancing
Radiometric differences between images can cause a patchwork effect
in a mosaic. Color balancing evens out the color contrasts from one
image to another to reduce the visibility of the seams and produce a
visually appealing mosaic.
Applying Color Balancing during Automatic Mosaicking
When you select Entire Image, OrthoEngine builds histograms for
each image, determines the optimum radiometry for the final mosaic,
and applies the transformation starting from the center of the mosaic.
When you select Overlap Area, OrthoEngine generates histograms for
all the overlapping areas in the mosaic, performs a least squares
analysis to determine the optimum radiometry for the final mosaic, and
then builds a transformation for each image as it is added to the mosaic.
Applying Color Balancing during Manual Mosaicking
The color balancing in Manual Mosaicking is based on the samples that
you identify in the overlap between the images already mosaicked and
the image that you are adding to the mosaic. OrthoEngine uses these
samples (match areas) to compute a lookup table that will adjust the
color in the image that you are adding to match the images already
mosaicked.
Collect small match areas representing the different areas so the lookup
table can be used to accurately correct radiometric mismatches. For
example, collect a match area in green area to balance greens, a match
area in dark area to match dark values, a match area in urban areas to
match urban areas, and so on. Using a single large match area covering
a large part of the image is effective only if you have an overall bright
or dark difference between the images.
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Changing the Layout in the Manual
Mosaicking Window
You can use Reapply Mosaicking to:
Select one of the following methods in the Layout list to determine
how you want to display the images in the viewer:
• Reproduce missing mosaic files.
• Interleave to display alternating lines from the images already
mosaicked and the image that you are adding to the mosaic. This
method is particularly effective when you want to view full color
images. Sharp, unstriped areas indicate where the features match well
and the radiometry is similar. The Layout list can contain Mosaic/
Interleave for grayscale images or Interleave Color, Interleave
Red, Interleave Green, and Interleave Blue so you can select the
channels for colored images.
• Overlay to display the images already mosaicked in red and the image
that you are adding to the mosaic in cyan. Sharp, grayscale areas
indicate where the features match well and the radiometry is similar.
The Layout list can contain Mosaic/Overlay for grayscale images or
Overlay Red, Overlay Green, and Overlay Blue so you can select
the channels for colored images.
• Double Window to display the images already mosaicked in the
viewer and the image that you are adding to the mosaic in a separate
window.
• Mosaic/Image/Reference to display the images already mosaicked in
red, the image that you are adding to the mosaic in green, and a
reference image in blue. The reference image can be any image that
overlaps the image that you want to add to the mosaic. Seeing where
and how the two images overlap can help you decide where to place the
cutline.
Regenerating the Mosaic
After the mosaic is complete, you may discover some areas that you
want to change. You can use Manual Mosaicking to edit the cutlines or
adjust the color balancing for the images as required, and then use
Reapply Mosaicking to reassemble the mosaic file.
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• Preview the mosaic.
• Regenerate the mosaic at different resolutions.
• Create a subset of the mosaic by changing the size of the Mosaic Area
and then regenerating the mosaic.
To regenerate the mosaic:
1. On the OrthoEngine window in the Processing Step list, select
Mosaic.
2. Click
the Reapply mosaicking icon.
3. On the Reapply mosaicking window, click in the Use column to select
or clear the images. Only images with check marks in the Use column
will be mosaicked. Use the arrow buttons to scroll through the list of
images.
4. Under Processing Options, select:
• Current Resolution to create the mosaic using the resolution set
in the Set Projection window.
• Different Resolution to set a new resolution for the mosaic (not
available in Mosaic Only projects). In the Mosaic Pixel Spacing
box, type the x pixel size. In the Mosaic Line Spacing box, type
the y pixel size.
Changing the resolution for the mosaic also changes the resolution in
the Set Projection window.
5. If available, you can select Regenerate stale orthos to update any
images labelled Stale in the Status column.
6. If available, you can select Delete newly generated orthos after
use to save disk space.
7. If available, you can click to remove the check mark beside Clear
mosaic file before starting to mosaic to add the images selected in
PCI Geomatics
Mosaicking Digital Elevation Models
the Use column to the existing mosaic file. To delete the images in the
mosaic file and reset the background to the default before adding the
selected images, select Clear mosaic file before starting to
mosaic.
8. Under Processing Start Time, click Start Now or Start at
(hh:mm) and set the time when you want the operation to begin
(within the next 24 hours).
9. Click Generate Mosaic.
Mosaicking Digital Elevation Models
Although you can use Automatic Mosaicking to unite digital elevation
models (DEMs), using DEM from raster file is designed specifically
for this purpose. For more information about using DEM from raster
file, see “Using Rasters to Generate a Digital Elevation Model” on
page 64.
If you do decide to use Automatic Mosaicking, set Color Balance to
None and choose Min Difference for the Cutline Selection Method.
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CHAPTER
10
Additional Features
Understanding the Enhancements
Enhancements make the image on the screen clearer and easier to
interpret without changing the values in the image file. The
enhancements available in the Enhance list change depending on the
viewer:
• None removes all the enhancements.
• Linear uniformly stretches the minimum and maximum values in the
image over the entire available output display range to enhance the
overall differences in gray levels in the image.
• Root compresses the range of higher values (brightness) and expanding
the range of lower values (darkness) so you can distinguish more detail
in darker areas of an image while still retaining some detail in the
brighter areas.
• Equalization or Equal distributes the values equally over the entire
output display range resulting in an almost uniform histogram. This
enhancement is effective in exposing details in the higher values
(brightness) and lower values (darkness), but causes less contrast in the
middle values.
• Adaptive combines the benefits of Equalization and Linear
enhancements resulting in a more natural display than Equalization
while effectively compensating for outliers.
• Infrequency assigns the values that occur the least frequently in the
image to the range of higher values (brightness) in the histogram so
finer details become brighter.
• Hold freezes the current appearance of the image, which improves the
loading speed of the image.
• Tail Trim to omit the upper and lower 2 percent of the image
histogram to remove outliers in the upper and lower part of the pixel
range. Tail Trim uses a 2 percent margin by default, but you can adjust
the amount of tail trim from 1 to 5 percent with Set Trim %.
• Exclude Min/Max disregards the lowest and the highest value in the
image histogram before applying the Tail Trim.
• Set Trim % to adjust the amount of tail trim from 1 to 5 percent.
Re-enhance
The enhancement is recalculated each time the zoom level is changed
by building a histogram with the range of values available in viewer
unless the viewer contains the Re-enhance button. Click the Re121
Chapter 10 - Additional Features
enhance button to recalculate the histogram using the range of values
existing in the viewer at the time that you applied the enhancement.
Press CTRL + left mouse button to zoom in, and CTRL + right mouse
button to zoom out.
Brightness
Reload
Brightness controls the overall luminosity (amount of light) in the
images. Click the arrow beside the Brightness icon to increase or
decrease overall luminosity.
Click Reload to update the image in the viewer and center it
around the cursor.
Pan
Contrast
Contrast controls the difference between the light and dark
extremes in the images. Click the arrow beside the Contrast icon
to increase or decrease the light and dark extremes.
Click Pan to move the image around with the cursor so that you
can view all the areas on it.
Loading Vectors Over an Image
Using Zoom, ReLoad and Pan
To import vectors:
Zoom
1. Click
Several ways are available for you to increase or decrease the
magnification of the image. The zoom features available change
depending on the viewer:
Click Zoom to Overview to decrease the magnification so the
whole image appears in the viewer.
Click Zoom In or press PAGE UP to increase the magnification
by increments. Click Zoom Out or press PAGE DOWN to
decrease the magnification by increments.
Click Zoom Interactive and drag a rectangle over the area you are
interested in magnifying.
Click Zoom 1:1 Image Resolution to adjust the magnification so
that one screen pixel displays one image pixel.
the Open new or existing photo icon
For information how to open an image, see “Opening Images” on
page 17.
2. Open an orthorectified or geometrically corrected image.
3. Click the
Load Vector icon.
4. On the General Vector Information window, click Load and
choose a file containing vectors for the area covered by the image.
5. Select the appropriate segment and click Load or Load & Close.
To hide a vector layer:
Check marks under Show indicate visible vector layers. To hide a
vector layer, click under Show to remove the check mark.
Press PAGE UP to increase the magnification by increments or press
PAGE DOWN to decrease the magnification by increments.
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PCI Geomatics
Cursor Control
Changing the Color of a Vector Layer
To change the color of the vectors
1. Click under Color beside the layer that you want to change.
• Type new coordinates under Geocoded or User Defined
Projection. The cursor will move to that exact location in the
viewer.
• Change the projections under Geocoded or User Defined
Projection to view the cursor location in different projections.
2. Select one of the following to choose a color:
• Click a color under Basic Colors.
Changing Image Color Channels
• Click a color under Color Continuum.
You can select which image channels as a red, green, or blue color
using the RGB Image Mapper.
• In the Model list, select a color model and adjust the color values
as required. Each color model offers different color values. For
Gray type or select the gray level. For RGB type or select the
red, green, and blue values. For CMYK type or select the cyan,
magenta, yellow, and black values. For HLS/IHS type or select
the hue, lightness, and saturation values.
3. Under Intensity, move the slider to determine the strength of the
color.
4. Click OK.
To place your cursor:
the Open new or existing photo icon
For information how to open an image, see “Opening Images” on
page 17.
2. Click the
1. Click
the Open new or existing photo icon to open an image.
For information how to open an image, see “Opening Images” on
page 17.
2. Click the
Open RGB Mapper icon.
The RGB Mapping window opens displaying a list of all the available
image channels for the image.
Cursor Control
1. Click
To change the colors of an image layer:
Cursor Control icon.
3. You can:
• Click in the viewer to view the coordinates in the Cursor Control
window.
• Type new pixel (P) and line (L) coordinates under Raster. The
cursor will move to that exact location in the viewer.
OrthoEngine User’s Guide
3. Click under Red, Green, or Blue to select the color for the image
channels that you want to change.
4. Click Close.
Selecting Image Channels
If the image that you are opening contains several channels, you will
have the choice of which ones you want to display in your project.
When the Database Channels window opens, click up to three
channels to be displayed in the viewer. You can change which image
channels are mapped to which channel in the viewer using the RGB
Mapper (see “Changing Image Color Channels” on page 123).
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The Average Image feature controls how the image pixels are
displayed in the viewer. One screen pixel can represent many image
pixels. Normally, OrthoEngine simply chooses an image pixel value to
represent the group being mapped to the screen pixel. Average Image
calculates the average value of that group of image pixels and uses that
value for the screen pixel. This process is also known as block
averaging. This process often produces more meaningful
representation of the image in the viewer.
Removing Images
When you remove an image from the project, the ground control
points, tie points, fiducial marks, and so on are removed as well.
However, you cannot delete an image if it means that a tie point will
remain without a matching point on another image. For example, if a
tie point is collected on two images, neither image can be removed
unless the tie point is removed. On the other hand, if the tie point is
collected on three images, then one image can be removed without
affecting the others.
• Remove photo from project and delete files on disk to delete
the image from both the project and the disk.
6. Click Close.
Re-connecting Offline Images
An image with the status Offline often means that the image was
deleted or moved to another location. If you changed the image’s
location, you can re-establish the connection between the project and
an Offline image with Rename Image/Photo or Sync Image/Photo
from the Utilities menu.
Renaming Images
You can also use the Rename Image/Photo feature to change the
Photo ID of an image.
To rename an image from the project:
To remove an image from the project:
1. In the main menu, click Utilities.
1. In the main menu, click Utilities.
2. Click Rename Image/Photos.
2. Click Remove Image/Photos.
3. Select:
3. Select:
• Uncorrected Photos to select a raw image.
• Uncorrected Photos to select a raw image.
• Ortho Photos to select an orthorectified image or geometrically
corrected image.
• Ortho Photos to select an orthorectified image or geometrically
corrected image.
• Epipolar Photos to select an epipolar pair.
• Epipolar Photos to select an epipolar pair.
4. Select one or more image from the list.
5. Click:
• Remove photo from project to remove the image from the
project, but leave the image on the disk
4. Click an image from the list.
5. You can:
• Type a new label for the image in the Photo ID box
• Type a new path in the Photo File box
• Click Browse to select the file.
6. Click Close.
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PCI Geomatics
Replacing Image Pixel Values
Synchronizing the Images
To replace values:
The Sync Image/Photos feature refreshes the link between the images
and the project as long as the paths remains the same. For example, if
your images are stored on multiple CDs instead of on the disk, some of
your images will appear as Offline when the corresponding CD is not
available. Using Sync Image/Photos re-establishes the link.
1. In the main menu, click Utilities.
To re-connect Offline images:
1. Open a project.
4. Click Channel and select channels from the list or click All
Channels.
2. In the main menu, click Utilities.
5. In Replace Option, click:
3. Click Sync Image/Photos.
4. Click Yes to re-establish the link.
Tip
If the images do not change from Offline to Online, the images may no
longer be in the same location. Use Rename Image/Photo to define the
path, “Renaming Images” on page 124.
2. Click Replace Image/Photos Values.
3. In Image File, type the path for the image or click Browse to select
the file.
• < to replace all values less than the value set in Value to
Replace.
• <= to replace all values less than or equal to the value set in
Value to Replace.
• = to replace all values equal to the value set in Value to Replace.
• >= to replace all values greater than or equal to the value set in
Value to Replace.
• > to replace all values greater than the value set in Value to
Replace.
Replacing Image Pixel Values
6. In Value to Replace type the number that you want to change.
To replace the pixel values in an image, you must know your images
very well and understand the consequences of performing this
function. You are affecting the image directly, not just the values held
in memory. OrthoEngine will identify all the instances of the selected
values in the image and replace them with the new values.
7. In Skip Value type the number in the selected range that you do not
want replaced.
However, you may find this function useful in some situations. For
example, if you are creating a mosaic with images containing different
background values, you can replace the background values of each
image so that they are all the same. Once the background value of all
the images is the same, you can create the mosaic without difficulty,
see “Mosaicking Images with a Background Value Other Than Zero”
on page 113.
OrthoEngine User’s Guide
8. In New Value type the number that you want to use instead.
9. In the New Value list, select:
• Replace to replace all the image pixel values equal to the Value
to Replace by the New Value.
• Add to add the New Value to all the image pixel values equal to
the Value to Replace.
• Subtract to subtract the New Value from all the image pixel
values selected using the Value to Replace.
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• Multiply to multiply by the New Value all the image pixel
values selected using the Value to Replace.
• Divide to divide by the New Value all the image pixel values
selected using the Value to Replace.
10. Click Replace Photo Value.
Converting the DEM Datum
The elevation reference in the digital elevation model (DEM) must
match the elevation reference of the imagery that you want to
orthorectify. Elevation values can be referenced to a number of
different surfaces, but for mapping operations you usually use
elevations above Mean Sea Level (MSL), which is based on the geoid.
For most math models, the model is based on ground control points that
are also based on the geoid.
Two math models are based on orbital information instead of ground
control points: the RADARSAT Specific Model and the Rational
Functions model when it is used with the IKONOS GEO Ortho Kit
product. Orbit information is always referenced to an ellipsoid, and the
ellipsoid number is taken from the projection information defined in
the file.
A DEM extracted from satellite imagery using the above math models
is based on an ellipsoidal model of the earth, not the geoid. The
difference between elevations relative to the ellipsoid and those
relative to the geoid can be significant—up to 107 meters in some
areas.
Therefore, you must make sure that the elevation reference of the DEM
matches the elevation reference of the imagery.
To perform a conversion between Ellipsoid and MSL, OrthoEngine
calculates the difference between the geoid and the ellipsoid at the
point in question, and then applies the difference to compute the
transformed elevation.
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To convert the DEM datum:
1. In the main menu, click Utilities.
2. Click Convert DEM Datum.
3. In DEM File, type the path for the DEM or click Browse to select the
file.
4. Click Channel and select channels from the list or click All
Channels.
5. Click:
• Ellipsoidal to MSL to convert the Ellipsoid elevations to Mean
Sea Level elevations.
• MSL to Ellipsoidal to convert the Mean Sea Level elevations to
the Ellipsoid elevations.
6. In Skip Value type the number that you do not want converted, such
as the background value.
7. Click Close.
Rejoining (Stitching) Image Tiles
Some ASTER, IKONOS, QuickBird, and SPOT images may be
delivered to you as image tiles. If the image tiles were cut from a strip
of data acquired on the same day in a single pass of the satellite, you
can stitch the tiles into one image and rebuild the orbital data for the
whole strip. Therefore, you can work with one large image instead of
working with several smaller images, which offers some advantages:
• Less images to orthorectify and mosaic.
• Fewer ground control points (GCPs) to collect since you have to
compute fewer math models.
• More coverage by the math model by bridging over obscured areas,
such as areas under cloud cover, where you cannot collect GCPs.
PCI Geomatics
Setting the Automatic Backup
However, computing the math model on the image tiles may provide
better fit to the ground control than a math model for a large scene.
You can stitch the following products:
• ASTER level 1A data
• SPOT level 1A data
• IKONOS GEO product
• IKONOS GEO Ortho Kit product
• QuickBird Basic product
To stitch images:
1. Start a satellite project, see “Starting a Project Using the Satellite
Orbital Math Model” on page 10.
2. Save the image tiles on your disk, see “Reading Satellite Images from a
CD or a Digital Distribution Format” on page 15.
3. In the main menu, click Utilities.
4. Click Stitch Image Tiles.
5. In Satellite, click the sensor type.
6. OrthoEngine uses the orbital data to sort and join the correct tiles so
you can enter the files in any order. In the Image File boxes, type the
paths and filenames of your imagery or click Browse to select the files.
7. In the Output Filename box, type the path and filename for your
reassembled image or click Browse to select a location.
8. Click Stitch.
Once the stitching is completed successfully, you have the option of
keeping or removing the tiles from your project.
OrthoEngine User’s Guide
Setting the Automatic Backup
The default backup saves the project every 10 minutes in a temporary
file with a .bk extension in the same folder as the project. The backup
file is deleted when you exit OrthoEngine normally. You can change
the frequency of the backup as required.
To set the Automatic Backup timer:
1. In the main menu, click Options.
2. Click Auto Backup.
3. Select Auto Timed Backup to enable the timer.
4. In enabled type the number of minutes and seconds to elapse between
backups.
5. In Auto Backup File type the filename of the backup file.
6. Click Close.
Setting Default Ground Control Point
Elevation Units
After you set the projection for your project, the same projection and
units of measurement for the elevation are set by default for ground
control point (GCP) collection. In some cases, however, the units of
measurement in the digital elevation model (DEM) or other source that
you are using to extract the elevation for the GCPs may differ from that
set in your project. By setting the GCP Elevation Units, OrthoEngine
can convert the values for your project automatically.
For example, you have a project set in UTM projection in meters, but
your DEM is in UTM projection with elevations in feet. If you set the
GCP Elevation Units as feet, then OrthoEngine will convert the
values.
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To set the default units of measurement for GCPs:
2. Click GCP Elevation Datum.
1. In the main menu, click Options.
3. Click Mean Sea Level or Ellipsoidal of your GCP source.
2. Click GCP Elevation Units.
3. Click Meters or Feet as required.
Changing the Default Orthorectification or
Mosaic Output Format
Setting a Default Ground Control Point
Elevation Datum
By default the output for orthorectification, geometric correction, and
mosaicking is PCI Geomatics’s PCIDSK (.pix) format. However, you
do not have to work in PCIDSK format. You can import, process, and
export your images using the TIFF format.
The elevation reference for GCPs must match the elevation reference
of the imagery in your project. When you set the projection, the
elevation datum is set by default.If the source of your GCPs differs
from that set in your project, OrthoEngine can convert the values for
your project automatically.
Elevation values can be referenced to a number of different surfaces,
but for mapping operations you usually use elevations above Mean Sea
Level (MSL), which is based on a geoid.
Some software packages support the “tiled” format for images. This
format saves the image as a series of tiles so you can open the images
on screen more rapidly.
The “tiled” format does not produce image tiles that you can later
stitch together. This format is used solely to improve viewing
performance in other software programmes.
For most math models, the model is based on ground control points that
are also based on the geoid.
To change the default output format:
Two math models are based on orbital information instead of ground
control points: the RADARSAT Specific Model and the Rational
Functions model when it is used with the IKONOS GEO Ortho Kit
product. Orbit information is always referenced to an ellipsoid, and the
ellipsoid number is taken from the projection information defined in
the file.
2. Click Ortho/Mosaic Output Format.
To perform a conversion between Ellipsoid and MSL, OrthoEngine
calculates the difference between the geoid and the ellipsoid at the
point in question, and then applies the difference to compute the
transformed elevation.
To set the default for the datum:
1. In the main menu, click Options.
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1. In the main menu, click Options.
3. Click:
• PCIDSK to create a single file in the .pix format.
• GeoTIFF to create a single file in the GeoTIFF format.
• GeoTIFF 256 Tiled to save the image in the GeoTIFF format
stored as tiles measuring 256 pixels by 256 lines.
• GeoTIFF 512 Tiled to save the image in the GeoTIFF format
stored as tiles measuring 512 pixels by 512 lines.
• GeoTIFF 1024 Tiled to save the image in the GeoTIFF format
stored as tiles measuring 1024 pixels by 1024 lines.
• TIFF World to create a single file in the TIFF World format.
PCI Geomatics
Setting the Channel Type for Your Output Image
• TIFF World 256 Tiled to save the image in the TIFF World
format stored as tiles measuring 256 pixels by 256 lines.
• TIFF World 512 Tiled to save the image in the TIFF World
format stored as tiles measuring 512 pixels by 512 lines.
• TIFF World 1024 Tiled to save the image in the TIFF World
format stored as tiles measuring 1024 pixels by 1024 lines.
Setting the Channel Type for Your Output
Image
To set the channel type for the orthorectified or
geometrically corrected images:
1. In the main menu, click Options.
2. Click Ortho Channel Type.
3. Click:
• Same As Input to set the range of pixel values according to the
values in the raw images.
• 8 Bit Unsigned to set the range of pixel values in the images
from 0 to 255. The term 8 Bit determines the range of values by
calculating 2 to the eighth power (28), which equals 256.
Unsigned means it uses only positive integers, therefore, the range
is set from 0 to 255. This option takes the least amount of disk
space.
• 16 Bit Signed to set the range of pixel values in the images from
-32,767 to +32,767. The term 16 Bit determines the range of
values by calculating 2 to the sixteenth power (216), which equals
65,536. Signed means it uses both positive and negative integers,
therefore, the range is set from -32,767 to +32,767.
• 16 Bit Unsigned to set the range of pixel values in the images
from 0 to 65,535. The range of values is the same as explained for
16 Bit Signed, however, Unsigned means it uses only positive
integers, therefore, the range is set from 0 to 65,535.
OrthoEngine User’s Guide
• 32 Bit Real to set the range of pixel values that includes decimals
and positive and negative values. The term 32 Bit Real is a range
of real numbers that is expressed as -1.2E-38 to +3.4E+38. This
option takes the most amount of disk space.
Understanding When To Build Overviews
Overviews are created when you orthorectify, geometrically correct, or
mosaic your images. Although overviews quicken the display of your
images on your screen, they do add processing time when they are
created. Therefore, you need to decide which will benefit you the most,
viewing the images faster or processing the images faster.
For example:
• If you are orthorectifying 200 small images, you may decide not to
create overviews since small images take very little time to display on
screen and building overviews will add significantly to the processing
time.
• If you are orthorectifying two large IKONOS scenes, you may decide to
create overviews since large images take longer to display on screen
compared with the time that it will take to build the overviews.
To enable or disable the overviews:
1. In the main menu, click Options.
2. Click Build Overview.
3. Click:
• Build Overview to create overviews.
• No Overview to disable overview creation.
Exporting the Math Model
You can export the math model solution as a segment in the PCIDSK
file containing the raw image. You can use this feature to re-establish
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the computed math model in a future project or use it in projects
outside OrthoEngine.
To export the math model solution:
8. In the Format Description, type the format of the command string
used to express the coordinates or click a format in the Example
Formats list. For more information, see “Understanding Format
Descriptions for Text Files Containing GCPs” on page 133.
1. In the main menu, click Options.
9. Click Apply Format.
2. Click Export.
10. Click Accept.
3. Click Model.
11. Click Close
4. Select file to export.
5. In the Name box, type the label of the segment.
6. In the Description box, type a description for the segment.
7. Click Export.
To export the GCPs to a new segment in the image file:
1. In the main menu, click Options.
2. Click Export.
3. Click GCPs.
Exporting the Ground Control Points
4. Select file to export.
You can export the GCP coordinates to a text file or as a segment in the
PCIDSK file containing the raw image.
5. In Segment Information, click Save to new segment in photo
file.
To export the GCPs to a text file:
1. In the main menu, click Options.
2. Click Export.
6. In the Name box, type the label of the segment.
7. In the Description box, type a description for the segment.
8. Click Export.
3. Click GCPs.
To export the GCPs to an existing segment:
4. Select file to export.
1. In the main menu, click Options.
5. In Segment Information, click Save to text file.
2. Click Export.
6. Click Export.
3. Click GCPs.
7. In GCP Output File, type the path and filename with the extension
.txt for the file or click Select to select a location.
4. Select file to export.
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5. In Segment Information, click Save to existing segment in photo
file.
PCI Geomatics
Exporting the Exterior Orientation
6. Select segment.
2. In the main menu, click Options.
7. Click Export.
3. Click Export.
Exporting the Exterior Orientation
When you export the exterior orientation to a text file, the resulting file
contains the x, y, and z coordinates of the sensor, the Omega, Phi, and
Kappa values of the sensor, and the Photo ID of the image. For more
information about exterior orientation, see “Understanding Exterior
Orientation” on page 26.
To export the exterior orientation to a file:
1. In the main menu, click Options.
2. Click Export.
3. Click Ext Orientation.
4. In Report File, type a path and filename with the extension .txt or
click Select to choose a file.
5. Click:
4. Click Supresoft Format Data.
5. In Directory, type a path to the empty folder. If you do not know the
path, you can:
• Click Browse.
• Click Choose Directory.
• Select a folder.
• Click OK.
6. Click Write.
Changing the Default Color Ground
Control Points and Tie Points
To change the default color:
1. In the main menu, click Options.
• Append to add the information to an existing file.
2. Click Customize Colors.
• Overwrite to replace the information in the file with the new
information.
3. Click:
Exporting to Supresoft Format
You can export the exterior orientation, interior orientation, and
camera calibration data to a folder for use with Supresoft IMAGIS.
OrthoEngine will generate text files for each image in the project
containing the required information in a format supported by
Supresoft.
To export the text files to a folder:
1. Create an empty folder (directory).
OrthoEngine User’s Guide
• GCP Color to change the default color of the ground control
point (GCP) indicator as it appears in the viewer.
• TP Color to change the default color of the tie point (TP)
indicator as it appears in the viewer.
4. Click the color that you want.
Setting the Threshold Values for the Math
Models (Bundle Options)
The Residual errors in the Residual Report will help you determine if
the solution is good enough for your project. Residual errors are the
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Chapter 10 - Additional Features
difference between the coordinates that you entered for the ground
control points (GCPs) or tie points and where the points are according
to the computed math model. For more information about the Residual
Report, see “Troubleshooting the Math Model Solution” on page 56.
• General to include the filename and description of the project
from the Project Information window.
OrthoEngine recalculates the math model several times to find the best
possible solution. The best possible solution is determined when the
residual errors of the GCPs and tie points fall within the limit set in the
XYZ Threshold, the Angle Threshold, or until the limit in the
Number of Iterations is reached. By adjusting the thresholds, you
control the precision of the model.
• Camera Calibration to include the information from the
Standard Aerial Camera Calibration Information window
or Digital/Video Camera Calibration Information window.
• Output mosaic to include information about the features set for
the mosaic such as its resolution and bounds.
4. Under Photos, select the images that you want to include in the report.
Press SHIFT or CTRL and click to select more than one image.
5. Under Photo Information, select as required:
To change the threshold values:
1. In the main menu, click Options.
2. Click Bundle Options.
3. In Number of Iterations, type the maximum number of times that
OrthoEngine can recalculate the math model solution.
4. In the XYZ Threshold box, type the acceptable deviation in pixels for
the coordinates.
5. In Angle Threshold type the acceptable deviation in degrees for the
the Omega, Phi, and Kappa angles.
6. Click Close.
Generating a Project Report
• General to include general information about the images that you
selected such as the number of channels, the image size, details
about the orthorectified version of the image, and which digital
elevation model was used.
• Exterior orientation to include information about the x, y, and z
location of the camera and the orientation of the camera in omega
(the rotation about the x axis), phi (the rotation about the y axis),
and kappa (the rotation about the z axis).
• Satellite Model to include the position and orientation of the
satellite.
• Orbital data to include information about the sensor such as the
Field of View, View Angle, and Eccentricity.
• Geometric Model to include information about the math model
solution.
6. Under Point Information, select:
To generate a Project Report:
• Ground control points to include a list of the GCPs collected in
the selected images.
1. On the OrthoEngine window in the Processing Step list, select
Reports.
• Tie points to include a list of the tie points collected in the
selected images.
2. Click
• Fiducial marks to include the positions of the fiducial marks in
the selected images.
the Project report icon.
3. Under Project Information, select:
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7. Click Print to File.
PCI Geomatics
Saving the Project as a Template
8. In Report File, type the path for the text file or click Select to choose
a location.
9. Click Append to the report to an existing file or click Overwrite to
replace or create a file.
Saving the Project as a Template
When you save your project as a template, the template retains the
information that you entered in the Project Information window, the
Set Projection window, the Standard Aerial Camera Calibration
Information window, and the math model.
To save the project as a template:
1. Open a project.
2. In the main menu, click File.
3. Click Save as Template.
4. Type a filename in the File name box.
5. Click Open.
Using the File Utility
You can use the File Utility to view detailed information about selected
GeoGateway file and edit some of the information depending on the
GeoGateway format type and the read/write status of the file.
Viewing an Image Outside Your Project
To open an image that is not a part of your project:
1. Click File from the main menu.
2. Click Image View.
OrthoEngine User’s Guide
3. Select an image.
For information about the features available in the viewer, see
“Understanding the Enhancements” on page 121, “Using Zoom,
ReLoad and Pan” on page 122, “Loading Vectors Over an Image”,
“Cursor Control”, and “Changing Image Color Channels” on page 123.
Understanding Format Descriptions for
Text Files Containing GCPs
You can import or export ground control points (GCPs) to a text file.
Each line in the text file contains the data for one GCP. The line is
divided into fields separated by spaces, tabs, and/or commas. Each
field contains a piece of information about the GCP.
When you import or export the GCPs to a text file, you must identify
what the fields contain and in what order they appear. A Format
Description is a string representing the order and the contents of the fields.
Character descriptions:
I: the GCP’s identification number.
X: the geocoded X coordinate.
Y: the geocoded Y coordinate.
P: the pixel location of the GCP on the uncorrected image file.
L: the line location of the GCP on the uncorrected image file.
E: the elevation of the GCP.
D: data to be ignored.
For example, the string IXYE represents the layout where I is the
GCP’s identification, X and Y are the GCP’s geocoded x and y
coordinates, and E is the GCP’s elevation.
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The line in the text file and the Format Description must match. Lines
that do not match the Format Description are ignored.
Fields can contain text, alphanumeric values, integers, decimals, or
exponential values (for example: 1.234+E05). Latitude and Longitude
values must appear in decimal degrees (123.5) rather than DMS form
(123 30 00). To include a phrase in a field, place the phrase in double
quotes.
If the field contains a numeric value ending with text, the text is
ignored. For example, N or W in Latitude and Longitude values are
ignored, therefore, use a negative sign instead.
Tip
Since latitude (north/south) usually appears before the longitude (east/
west), use YX instead of the more common XY.
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PCI Geomatics
CHAPTER
11
Creating a Chip Database
Understanding the Chip Manager
A chip database is a compilation of individual image samples, called
chips, usually measuring 256 pixels by 256 pixels or smaller. Each
image section contains an accurate geocoded location and metadata,
such as which sensor it was generated from, the date it was acquired,
the viewing angle, and so on.
These chips, can be used to collect ground control points (GCPs). You
can visually match a feature in the raw image that you are
georeferencing and use the coordinates from the chip database as a
GCP or use the chips to automate the collection of GCPs. For more
information, see “Collecting Ground Control Points from a Chip
Database Manually” on page 40.
With the Chip Manager, you can create new chip databases, add or
remove chips from existing chip databases, and merge different chip
databases.
You can use the chips to collect ground control points (GCPs) on the
raw images in your project as explained in “Collecting Ground Control
Points from a Chip Database Manually” on page 40.
Opening the PCI Chip Manager
To open the Chip Manager, choose one of the following:
1. From Windows®, click the Start button, click Programs, click PCI
Geomatica V9.0, and then click Chip Manager.
2. If Geomatica is running, click
Geomatica Toolbar.
the ChipMan icon on the
3. For Unix® after you have set up the path for Geomatica, type in the
prompt: chipman.exe
Creating a New Database
To create a new database:
1. In the main menu click File.
2. Click New.
135
Chapter 11 - Creating a Chip Database
3. In the Chip Database name box, type the filename for your new
database.
4. Click OK.
Next step in your project . . .
See “Selecting the Source for the Chips” on page 136.
Opening an Existing Chip Database
You can open an existing chip database and add new chips.
To open a chip database:
1. In the main menu click File.
2. Click Open.
3. Select your file.
Next step in your project . . .
See “Selecting the Source for the Chips” on page 136.
Selecting the Source for the Chips
The source image is a geocoded image that you use to create the chips.
You can create several chips from one image. If the image contains an
orbit segment, OrthoEngine can extract information required to
complete the Default Parameter Settings window. Otherwise, type
the information required manually.
2. Click Source Image.
3. Select the image.
4. On the File window under Database Channels, click the channel that
you want. For more information, see “Importing Images or
Photographs into Your Project” on page 15.
5. Click Load & Close.
On the Default Parameter Settings window, enter the sensor
information for the image. If you are going to create many chips from
the same image, you can set the information as a default, see “Setting
the Source Image Default Parameters” on page 140.
6. In the Sensor box, type the name of the sensor or select the sensor
from the list.
7. In the Viewing Angle box, type the angle in degrees between the axis
of the sensor and the ground.
8. In the Acquisition Date box, type the day, month, and year that the
image was taken.
9. In the Resolution boxes, type the x pixel size and the y pixel size in
the units used in the image.
10. In the General Description box, type a description that will help you
identify the chip.
11. In the Scene Description box, type the Scene ID.
12. Click Accept.
Next step in your project . . .
See “Collecting the Chip” on page 137.
To open the image:
1. In the main menu click File.
136
PCI Geomatics
Working in the Chip Manager Viewers
Working in the Chip Manager Viewers
The Chip Manager contains two viewers. The viewer on the PCI
ImageChipsManager window displays the current chip in the database.
The other viewer displays the source image. For more information about the
features in the viewers, see “Understanding the Enhancements” on page 121
and “Using Zoom, ReLoad and Pan” on page 122.
Changing the channel display for the chip viewer:
On the PCI ImageChipsManager window, select RGB color bands or
individual bands in black and white in the Imagery list as required.
6. In Save Option, click:
• Chip Only if you want to save the chip without the overview.
• Chip and Overview if you want to save the chip with the
overview. In the list select the size of the overview window. The
overview provides a view of the area surrounding the chip.
7. In the Chip ID box, type the label for the chip.
8. You can extract the elevation for the GCP in two ways:
Switching between the Chip and the Overview
• On the PCI ImageChipsManager window, click Select near
the bottom of the window and open a digital elevation model
(DEM) that covers the area of your source image. Click Extract
Elevation.
On the PCI ImageChipsManager window, click Chip to view only
the chip or click Overview to see more of the area surrounding the
chip.
• If you have your source image and its DEM in the same file, click
Elevation channel, click the DEM channel on the Elevation
Channel Selection window, and click Close.
Collecting the Chip
The elevation of the point that you selected in the source image is
transferred to the window under Ground Control Point
Information.
To collect a chip from an image:
1. Open the source image, see “Selecting the Source for the Chips” on
page 136.
9. In the +/- boxes beside the Elev box, the Easting box, and the
Northing box, type the estimated error for each.
2. At a zoom level where you can see the detail in the source image,
position the cursor precisely on the feature that you will use as a GCP.
3. Click New chip.
4. On the viewer displaying the source image, click Chip Size and
specify the size of the chip. For more information, see “Determining
the Size of the Chip” on page 137.
5. On the PCI ImageChipsManager window, click Accept GCP
from cursor.
10. In the list beside +/- box for the Elev box, select Meter or Feet.
11. Click Save chip.
Determining the Size of the Chip
The cursor at the center of the chip outline becomes the ground control
point (GCP) when you save the chip in the database.
The coordinates of the GCP in the source image are transferred to the
window under Ground Control Point Information.
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Chapter 11 - Creating a Chip Database
To change the size of the chip footprint:
1. In the viewer displaying the source image, click Chip Size. The
default chip size is 64 by 64 pixels. The maximum chip size is 256 by
256 pixels.
2. Select one of the following:
• Type the number of pixels and lines in the Size boxes.
• Click Drag out square on image and drag a square over the area
that you want on the source image.
• Click Drag out rectangle on image and drag a rectangle over
the area that you want on the source image.
3. Click Close.
Creating Chips from a GCP Segment
You can create chips from an image that contains a ground control
point (GCP) segment. A GCP segment is a channel included in an
image file that contains the x and y coordinates, the pixel and line
coordinates, and the elevation for GCPs in the image. You can use only
GCP segments that contain a pair of UTM coordinates and pixel and
line coordinates to create chips.
6. Under GCP List, click a GCP, and click Use Selected GCP as
Chip.
7. On the viewer displaying the source image, click Chip Size and
specify the size of the chip. For more information, see “Determining
the Size of the Chip” on page 137.
8. On the PCI ImageChipsManager window in Save Option, click:
• Chip Only if you want to save the chip without the overview.
• Chip and Overview if you want to save the chip with the
overview. In the list select the size of the overview window. The
overview provides a view of the area surrounding the chip.
9. In the Chip ID box type the label for the chip.
The Sensor, Acquisition, General ID, and Scene ID boxes should
be filled automatically with the information you provided when you
opened the source image.
10. If you have a DEM, click Extract Elevation to extract the elevation
value for the GCP. If you do not have a DEM, the elevation value may
appear in the GCP list on the GCP Segment File window.
11. In the +/- boxes beside the Elev box, the Easting box, and the
Northing box, type the estimated error for each.
To create a chip from a GCP segment:
1. Create or open a database. For more information, see “Creating a New
Database” on page 135 or “Opening an Existing Chip Database” on
page 136.
12. In the list beside +/- box for the Elev box, select Meter or Feet.
2. Open a source image that contains a GCP segment. For more
information, see “Selecting the Source for the Chips” on page 136.
13. Click Save chip.
3. In the main menu click Utilities.
Changing the Location of the GCP
4. Click Use GCP Segment, and click From Image.
You can change the location of the ground control point (GCP) on an
existing chip.
5. Select a segment.
138
PCI Geomatics
Searching the Chip Database
To change the location of the GCP on the chip:
2. In the main menu, click Utilities.
1. On the PCI ImageChipsManager window, click on the new location
for the GCP.
3. Click New from search list.
2. Click Accept GCP from cursor.
4. In the New chip database name box, type the path and filename for
the new database or click Browse to select the file.
3. Click Save chip.
5. Click Create Database.
To undo the change, click Cancel.
Merging Chip Databases
Searching the Chip Database
Copies of each chip database are combined into one chip database.
To search the chip database:
To merge two chip databases:
1. On the PCI ImageChipsManager window, do one of the following:
1. In the main menu, click Utilities.
• Click the # button, type the chip ID or chip sequence number, and
then click OK.
2. Click Merge image chips.
• Use the navigation buttons to select the chip.
3. In the 1st database box, type the path of one of the chip databases or
click Select to choose the file.
• In the main menu click Utilities and click Search image chips
to narrow the search for chips to a manageable number. For
information about searching the chip database, see “Searching for
Chips in a Database” on page 42 and start with step 2.
4. In the 2nd database box, type the path of the other chip database or
click Select to choose the file.
• Type the chip ID in the Chip ID box under Current Chip Info
and then press ENTER.
5. In the Merged database box, type the path and filename of the new
chip database or click Select to choose a location.
Click More Info to view detailed header and chip information.
6. Click Perform Merge.
Creating a New Chip Database from an
Existing Database
After searching an existing chip database, you can save a copy of the
selected chips in a new database.
7. Click Close.
Deleting a Chip Database
To delete a chip database from the disk:
To create a chip database from the chips:
1. In the main menu, click Utilities.
1. Perform a search. For more information, see “Searching the Chip
Database” on page 139.
2. Click Delete.
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Chapter 11 - Creating a Chip Database
3. Select a chip database and click Open.
Generating Reports
4. Click Yes to delete the database.
The Current Chip report produces information about the chip
displayed in the PCI ImageChipsManager window. The report
provides information such as the Chip ID, sensor type, view angle,
acquisition date, scene ID, general ID, GCP location and elevation,
chip size, resolution, number of image channels, data type of the image
channels, the source file from which the chip is extracted, and so on.
Deleting a Chip from the Database
To delete a chip from a chip database:
1. Open a database. For more information, see “Opening an Existing Chip
Database” on page 136.
2. Select the chip that you want to delete. To search the database, see
“Searching the Chip Database” on page 139.
3. At the bottom of the PCI ImageChipsManager window, click
Delete chip.
The chip that appears in the chip viewer is deleted.
The Summary report provides information such as creation date and
time, date and time of the last update, database name, and the number
of chips of each type of sensor in the database.
To produce a report:
1. Open a database. For more information, see “Opening an Existing Chip
Database” on page 136.
2. In the main menu, click Utilities.
4.
Click Yes to delete the chip.
Defragmenting a Chip Database
As chips are deleted from the chip database, the gaps in the database
remain. Defragmenting the chip database reduces the amount of disk
space it occupies.
To defragment the chip database:
1. Open the database that you want to defragment. For more information,
see “Opening an Existing Chip Database” on page 136.
2. In the main menu, click Utilities.
3. Click Pack.
4. Click Yes to defragment the database.
140
3. Click Reports.
4. Click:
• Current Chip to produce a report about the displayed chip.
• Summary to produce a report about the chip database.
5. Click:
• Close to close the report without saving it.
• Save to File to save the report in a text file.
Setting the Source Image Default
Parameters
If you are going to create many chips from the same image, you can
enter defaults in the Default Parameter Settings window.
PCI Geomatics
Changing the Colors of the Cursors
To set the defaults:
To mix your own color:
1. From the main menu click Preferences, and click Default.
1. In the main menu click Preferences, and click Colors.
2. In the Sensor box, type the name of the sensor or select the sensor
from the list.
2. In the Chip Cursor Color list or Chip GCP Color list, click Mix
Color.
3. In the Viewing Angle box, type the angle in degrees between the axis
of the sensor and the ground.
3. Move the sliders for Red, Green, and Blue, or type the color values
that you want in the corresponding boxes until you have the desired
color.
4. In the Acquisition Date box, type the day, month, and year that the
image was taken.
4. Click Close.
5. In the Resolution boxes, type the x pixel size and the y pixel size in
the units used in the image.
6. In the General Description box, type a description that will help you
identify the chip.
7. In the Scene Description box, type the Scene ID.
8. Click Accept.
Changing the Colors of the Cursors
To change the color of the cursor in the source image
viewer:
1. In the main menu click Preferences, and click Colors.
2. In the Chip Cursor Color list, select the color that you want.
3. Click Close.
To change the color of the cursor in the chip viewer:
1. In the main menu click Preferences, and click Colors.
2. In the Chip GCP Color list, select the color that you want.
3. Click Close.
OrthoEngine User’s Guide
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Chapter 11 - Creating a Chip Database
142
PCI Geomatics
Index
Numerics
16 Bit Signed 112, 129
16 Bit Unsigned 112, 129
32 Bit Real 112, 129
3-D Feature Extraction
add lines 88
add points 88
add polygons 89
aligning the images 85
Anaglyph technology 82
change color of vectors 87
change order of layers 87
change projection 86
change type of vectors 88
change visibility of layers 87
completing the Attribute table 93
create a layer 85
delete a layer 94
delete line or polygon 92
delete vertex 91
designing the Attribute table 92
extracting lines from DEM 96
extracting points from DEM 95
import layers 87
insert vertex 91
metadata 92, 93
move vertex or point 92
navigating the 3-D viewer 84
OpenGL technology 82
reducing eyestrain 83
save a layer 93
select a 3-D stereo pair 84
Shortcuts for the 3-D viewer 94
Snap to Line 90
Snap to Vertex 90
understanding 81
undo 92
vector editing tools 90
work flow 83
3-D glasses
advantages and disadvantages 82
3D Lines 66
3-D stereo pair
selecting 84
8 Bit Unsigned 112, 129
143
-
A
Accepted Elevation Match Points 65
accuracy of the math model (number of GCPs) 34
Adaptive 121
add a tablet 48
Add image to mosaic 115, 116
Add lines 88
Add points 88
Add polygons 89
Add to DEM 65
Aerial Camera 9
Aerial Photography Math Model 5
minimum number of GCPs 34
Starting a project 9
understanding solution 55
affine model 43
Albany 27
aligning images in 3-D 85
Anaglyph technology 82
anchor the reference frame around point 45
angular orientation of the camera 55
Applanix 27
ASAR 10
DEM from stereo pairs 69
intro to OrthoEngine 1
minimum number of GCPs 34
supported formats 18
understanding Satellite Orbital Math Model 5
ASCII string 60
ASCII(n) 60
ASTER
DEM from stereo pairs 69
HDF format 18
intro to OrthoEngine 1
joining tiles 126
minimum number of GCPs 34
selecting left and right images 69
stitching 126
supported formats 18
understanding Satellite Orbital Math Model 5
144
Auto Locate 35
AutoCad 93
Automatic Backup 127
automatic bundle adjustment. See Bundle Update
automatic correlation 35
Automatic Mosaicking 113
Automatically collect GCPs from chip database 44
automatically collect tie point 53
Average 73
Average Filter 106
Average filter 70
Average Image 124
AVHRR
intro to OrthoEngine 1
understanding Satellite Orbital Math Model 5
B
Background Value 72, 75, 95, 112, 113
Backup 127
bad points 57
batch processing
DEMs 71
epipolar pairs 71
Baud Rate 46, 49, 61
BAUD(baud rate) 61
Bilinear Interpolation 105
black and white bands 43
Blending 117
block averaging 124
Bounds of DEM 67
Brazilian LANDSAT 5 18
breaklines 66
Brightness 116, 122
Build Overviews 129
bundle adjustment 55
Bundle Update 36
button characters 60
PCI Geomatics
C
calculation of a rigorous math model 55
calculation of a simple math model 56
Calibration Edge 25
camera calibration data 21
Camera Type 9
Canadian CDs LANDSAT 19
CAP-T format 20
CCDs 9, 24
CCD arrays 9
CCRS 69
CD Format 16
CD Header Filename 16
CD Image Filename 16
CD, read satellite images from 15
CEOS RADAR 16, 19
change color of vectors 87, 123
change GCP color 131
change GCP position on a chip 42
change image color channels 123
change location of GCP on a chip (Chip Manager) 138
Change Photo Orientation 30
change pixel values 125
change the color of cursor (Chip Manager) 141
change the color of GCP 43
change the projection for new layer 86
change the size of the chip (Chip Manager) 138
change the threshold values 132
change tie point color 131
Change to Check Point 59
change type of vectors 88
Changing the channel display (Chip Manager) 137
channel display (Chip Manager) 137
channel selection 43, 123
Channels
16 Bit Signed 112, 129
16 Bit Unsigned 112, 129
32 Bit Real 112, 129
8 Bit Unsigned 112, 129
Average Image 124
OrthoEngine User’s Guide
block averaging 124
change color 123
Database Channels 123
selecting 123
set channel type 129
Character descriptions 133
characters 60
Charged Coupled Devices. See CCDs
Check Point 36, 38, 39, 41, 47, 59
Check Points 57
chip 40
Chip Cursor Color (Chip Manager) 141
chip database 40, 135
Chip GCP Color (Chip Manager) 141
chip ID 41
Chip Information 24
Chip Manager 135
chip sequence number 41
Chip Size 24, 137, 138
choosing quality tie points 52
Clear Mask 76
Cliffs (2D) 66
Clip Region 30, 72
for extracting lines from DEM 96
for geocoding DEM 80
Cloud-Covered Areas 79
coefficients
Decentering Distortion 24
extract from file 11
Radial Lens Distortion 22, 24
Rational Functions 7
collect a chip from an image 137
collect GCPs
from chip database 40
from chip database automatically 43
from geocoded image 37
from tablet 45, 47
from vectors 39
manually 36
collect tie point automatically 53
145
-
collect tie point manually 52
collecting cutlines 114, 115
color balancing
automatic 114
manual 116
understanding 117
Colors (Chip Manager) 141
command string for tablet 49, 60
communication with tablet 46, 49, 60
computation of a rigorous math model 55
computation of a simple math model 56
Compute from GCPs 11
Compute from GCPs and tie points 10
Compute from Length 23, 24
Compute From Table 22, 24
Connect to Tablet 46, 49
Contact Information 4
contours 65
Contrast 122
convert DEM datum 126
copy chips (Chip Manager) 139
correcting images. See Orthorectification or Geometric Correction
correcting the DEM 75, 76, 77, 78
correlation between chip and image 44
correlation between stereo image pairs 69
correlation during DEM extraction 73
correlation score 45, 54, 72, 73
Correlation Threshold 45
CR 60
create a chip database 139
Create a mask 75
create a new chip database 135
Create Database (Chip Manager) 139
create epipolar images 69
Create Score Channel 72
Creating Chips from a GCP Segment 138
Cubic Convolution 105
cursor
place in viewer 123
Cursor Control 123
146
curvature of the earth 23, 24
Cutlines
collecting 114, 115
understanding 117
D
Data Bits 46, 49, 61
Data Snooping 59
data strip 26
remove 31
DATA(data bits) 61
Database channels 123
datum 12, 14
Decentering Distortion 22, 24
Default
Mosaic output format 128
Orthorectification output format 128
Default Parameter Settings 140
Default ROI to Image 43
Defaults
change GCP color 131
change tie point color 131
for GCP elevation datum 128
for GCP elevation units 127
set channel type 129
Define Clip Region 31
during DEM extraction 72
for extracting lines from DEM 96
for geocoding DEM 80
Define Output DEM file 67
define the size of the frame on tablet 47
defining the search parameters for chip database 42
defragment the chip database (Chip Manager) 140
Degree 28
Degrees Minutes Seconds. See DMS
delete a chip database (Chip Manager) 139
delete a chip from a chip database (Chip Manager) 140
delete a layer 94
delete line 90
Delete Point 59
PCI Geomatics
delete vertex 90
DEM
bounds 67
Cloud-Covered Areas 79
converting the datum 126
create epipolar images 69
Detail 74
editing 71, 74, 75, 76, 77, 78
editing strategies 78
Erode Holes 78
export to text file 80
extents 73
Finite Difference 68
Forests 78
from contours 66
from epipolar pairs 71
from points 66
from raster file 64
from stereo pairs 69
from TIN 66
from vectors 65, 67
Gaussian filter 78
geocode 71, 79
Interpolate 78
Lakes 78
Median filter 78
merge DEM raster files 64
Natural Neighbor Interpolation 68
No. of Iterations 68
Noise 79
Noise Removal 77
output 67
Pixel Sampling 74
replace elevation values under mask 76
resolution 67
size 67
Smooth filter 78
Switching between image and DEM 75
Tolerance 68
understanding 63
OrthoEngine User’s Guide
Urban Areas 78
use for elevation of GCPs 36, 38, 40, 42, 48, 51, 53, 54
using GCPs, tie points, and elevation match points 64
using rasters, vectors, or control points 67
Detail in DEM 72, 74
determining pixel value 73
determining the best solution for the math model 56
digital camera calibration 21
digital distribution format, read satellite images from 15
digital elevation model. See DEM
Digital/Video Camera 9
digitizing table 45, 47
Dimap format 20
Display Chips 42, 43
display image 17
display images 129
Display overall image layout 55
Display overall layout 54
Distortions
correct 55, 56
non-symmetric, see Decentering Distortion
pin paper map to tablet 45
radial, see Principal Point Offset
symmetric, see Radial Lens Distortion
distribute tie points 54
distribution format 16
DMS 28
DOQQs 64
DOQs 64
Double Window 118
downsampling 70
Drag out rectangle on image (Chip Manager) 138
Drag out square on image (Chip Manager) 138
E
Earth Model 13
Earth Radius 23, 24
Edge features 114
Edit Point 59
Editing the DEM 71, 75, 76, 77, 78
147
-
elements of exterior orientation 55
elevation match point
to generate DEM 64
Elevation Match Point Collection 65
Elevation Offset 100
Elevation Scale 100
ellipsoid 12, 14, 126
Enhancements
Adaptive 121
Equal 121
Equalization 121
Exclude Min/Max 121
Hold 121
Infrequency 121
Linear 121
recalculate 121
Root 121
Set Trim % 121
Tail Trim 121
understanding 121
Enter GPS/INS or exterior orientation data manually 29
Entire Image (mosaicking) 114
EOC
intro to OrthoEngine 1
minimum number of GCPs 34
EOSAT IRS 18
EOSAT LANDSAT 5 18
epipolar images 69
for 3-D stereo 82
Equal 121
Equalization 121
equation
Decentering Distortion 22
Earth Radius 23
Elevation Scale and Elevation Offset 100
Gaussian function 106
Photo Scale 23
Radar Enhanced Frost 108
Radar Enhanced Lee 110
Radar Gamma Filter 107
148
Radar Kuan 109
Radial Lens Distortion 22
Erode Holes 78
EROS
minimum number of GCPs 34
Errors
computed fiducial mark positions 25, 26
ERS
intro to OrthoEngine 1
minimum number of GCPs 34
supported formats 19
understanding Satellite Orbital Math Model 5
ESA CDs LANDSAT 19
ESC 60
ESRI Shape File 93
estimated error 37, 38, 40, 42, 48, 50, 53
estimated error (Chip Manager) 138
Example Formats 49
Exclude Min/Max 121
export
DEM to text file 80
exterior orientation 131
Format Descriptions 133
GCPs 130
math model 129
Project Report 132
Supresoft Format 131
extents of the DEM 73
Exterior Orientation 10, 26, 29, 131
extract DEM from epipolar pairs 71
Extract Elevation 51
Extract from Image File 11
extract the elevation for the GCP (Chip Manager) 137
Extracted Data table 29
eyestrain 83
F
Fiducial marks 23, 24
collect automatically 26
collect manually 25
PCI Geomatics
overwrite 26
File Utility 133
Fill all Failed 76
Fill Failed @ Cursor 76
[email protected] 76
Filter Size
for Radar Enhanced Frost 108
for Radar Enhanced Lee 110
for Radar Gamma Filter 107
for Radar Kuan 109
Filters
Average filter 106
Bilinear Interpolation 105
Cubic Convolution 105
Erode Holes 78
Gaussian filter 78, 106
Interpolate 78
Median filter 78, 106
Nearest Neighbor Interpolation 105
Noise Removal 77
Radar Enhanced Frost 108
Radar Enhanced Lee 110
Radar Gamma filter 107
Radar Kuan 109
SIN 8 Pt and 16 Pt SinX/X 105
Smooth filter 78
User Defined filter 106
Finite Difference 68
flying height 55
Focal Length 21, 24
Forests 78
Format Description 49
Format Descriptions 133
Format String 49, 61
Format string rules 60
Format Strings for tablet 60
FORMAT(format string) 61
G
gaps in DEM. See Interpolate Holes
OrthoEngine User’s Guide
Gaussian Filter 106
Gaussian filter 78
GCP
change color in chip 43
change default color 131
choosing quality points 34
collect GCPs from chip database 40
collect GCPs from chip database automatically 43
collect GCPs from geocoded image 37
collect GCPs from tablet 45, 47
collect GCPs from vectors 39
collect GCPs manually 36
defaults for GCP elevation datum 128
display layout 54
export 130
import from file 49
minimum number 34
setting GCP Elevation Units 127
understanding 33
using GCPs to generate DEM 64
GCP Projection 13
GDB 1
generate epipolar images 69
generate Project Report 132
Generating Reports (Chip Manager) 140
Generic Database. See GDB
generic image file 17
GEO product 18
geocode DEM 79
automatic batch processing 71
geocoded image 37
Geometric Correction
processing the images 101
resampling options 104
Sampling Interval 102
set channel type 129
Status Descriptions 103
understanding 100
geometry for stereo pairs 69
geometry of the camera 55
149
-
GeoTIFF 128
GeoTiff format 18
Global Positioning Systems. See GPS/INS 10
GPS/INS 10, 26, 28
See also Photo Scale 23
Grads 28
grayscale bands 43
Grid Pinning 45
ground control point. See GCP
GTOPO30 DEM 19
guidelines 31
H
HDF format 18
header file 16
high residual errors 57
high resolution sensors 10
Highest Score 73
Hold 121
Holes 64, 72, 80
Hot Spot removal 114
How To Reach Us 4
I
Identifying Errors in the Math Model 57
IKONOS
converting the DEM datum 126
DEM from stereo pairs 69
intro to OrthoEngine 1
joining tiles 126
minimum number of GCPs 34
setting the GCP elevation datum 128
stitching 126
supported formats 18
understanding Rational Functions Math Model 7
understanding Satellite Orbital Math Model 5
using the right math model 6
Image Format
for Radar Enhanced Frost 108
150
for Radar Enhanced Lee 110
for Radar Gamma Filter 107
for Radar Kuan 109
import
Average Image 124
channels 124
digital images 15
exterior orientation 10, 28
Format Descriptions 133
GCPs, tie points, and elevation match points to generate DEM 64
GPS/INS 28
Import Exterior Orientation Data from Text File 28
Import GCPs from File 49
Import GPS/INS Data from Text File 28
Import GPS/INS or exterior orientation data from file 28
layer in 3-D viewer 87
Mosaic Area 112
photographs 15
raster to generate DEM 64
rasters, vectors, or control points to generate DEM 67
satellite data from PCIDSK 17
satellite images 15
triangulation solution 27
vectors 122
video images 15
Import & Build DEM 64
IMU. See Inertial Measurement Unit
Inertial Measurement Unit 27
Infrequency 121
Initialization 49
INITIALIZE(init string) 61
Input Exterior Orientation Data Manually 29
Input GPS/INS Data Manually 29
Input Vector Layer 66
Input window 80, 96
insert vertex 90
interior orientation 21
Interleave 118
Interpolate 78
Interpolate Holes 64
PCI Geomatics
IRS
DEM from stereo pairs 69
intro to OrthoEngine 1
minimum number of GCPs 34
supported formats 18
understanding Satellite Orbital Math Model 5
J
JERS
intro to OrthoEngine 1
minimum number of GCPs 34
supported formats 18
understanding Satellite Orbital Math Model 5
joining image tiles 126
K
kappa 27, 55
rotate 27, 29
Kernel File 106
L
Lakes 78
LANDSAT
intro to OrthoEngine 1
minimum number of GCPs 34
selecting NLAPS CD Format 16
supported formats 18
understanding Satellite Orbital Math Model 5
Last Value 73
Layer
add lines 88
add points 88
add polygons 89
change order 87
change projection 86
create layer for 3-D vectors 85
delete 94
import 87
save 93
OrthoEngine User’s Guide
show/hide 87
layout of string 50
LF 60
LGSOWG JERS1 18
LGWOWG SPOT (Canadian format) 19
Line Drawing Width 76
Line Spacing 14
Linear 121
Lines 66, 88, 96
Load vectors 122
Low Resolution 10
M
Manual Mosaicking 115
manually collect GCPs 36
manually collect tie point 52
map north 27
Map Tie-down 46
MAP-ORIENTED product 18
masks 75
Match Channel 44
Match Chips 44
matching features on chips 45
Matching Threshold 54
Math model
Aerial Photography 5, 9
change threshold values 132
export 129
None (Mosaic Only) 12
number of iterations 132
performing bundle adjustment 55
Polynomial 7, 11
Rational Functions 6, 11
Residual Report 58
Satellite Orbital 5, 10
Thin Plate Spline 8, 12
troubleshooting the solution 56
understanding bundle adjustment 55
understanding the solution for Polynomial math model 56
understanding the solution for Rational Functions math model 56
151
-
understanding the solution for rigorous models 55
understanding the solution for simple models 56
understanding the solution for Thin Plate Spline math model 56
using right model for IKONOS 6
Math Modelling Method. See Math model
Mean Sea Level (MSL) 126
Median Filter 106
Median filter 71, 78
merge chip databases 139
merge DEM raster files 64
Merge image chips (Chip Manager) 139
Merged database (Chip Manager) 139
MERIS
intro to OrthoEngine 1
Min Difference 114
Min Relative Difference 114
minimum number of GCPs 34
Mix Color (Chip Manager) 141
mix your own color for cursor (Chip Manager) 141
Mode filter 71
Model Calculations 56
modify a tablet 48
Mosaic Area 112
add image 116
editing Mosaic Extents 113
select existing 112
Mosaic Extents 113
mosaic file. See Mosaic Area
Mosaic/Image/Reference 118
Mosaic/Overlay 118
Mosaicking
add image 115, 116
automatic 113
blending the seams 117
collecting cutlines 115
color balancing 116, 117
default output format 128
defining Mosaic Area 112
DEM 119
Double Window 118
152
images with Background Value other than zero 113
Interleave 118
manual 115
Mosaic Area 112
Mosaic/Image/Reference 118
None (Mosaic Only) 112
Overlay 118
Reapply Mosaicking 118
understanding 111
understanding color balancing 117
understanding cutlines 117
move vectors 90
N
NAME(tablet name) 61
Natural Neighbor Interpolation 68
navigating the 3-D viewer 84
navigation solution 10
Nearest Neighbor Interpolation 105
New
Aerial Photograph project 9
Mosaic Only project 12
Polynomial project 11
Rational Functions project 11
Satellite project 10
Thin Plate Spline project 12
New chip 137
New chip database name box (Chip Manager) 139
New Photo 15
NITF file 11
NITF format 18, 19
NLAPS LANDSAT 5 19
No Data. See Background Value
No. of Coefficients 36, 38, 39, 41
No. of Iterations 68
No. of Tie Points per Area 53
Noise 79
Noise Removal 77
nominal scale 24
None (Mosaic Only) 112
PCI Geomatics
non-symmetric distortion. See Decentering Distortion
Normalization 114
normalized residual errors 59
north 27
number of GCPs 34
Number of Looks
for Radar Enhanced Frost 109
for Radar Enhanced Lee 110
for Radar Gamma Filter 107
for Radar Kuan 109
number of tie points per area 53
O
Offline
reconnecting 124
omega 27, 55
open an existing chip database 136
open an image 17
Open new or existing photo 15, 17
Open Photo 17
OpenGL technology 82
Opening the PCI Chip Manager 135
orbit information. See Read satellite images
ORBIT-ORIENTED product 18
orientation of the camera 27
orientation of the sensor 55
Orthorectification
default output format 128
Elevation Offset 100
Elevation Scale 100
processing the images 98
resampling options 104
Sampling Interval 102
set channel type 129
Status Descriptions 103
troubleshooting 104
understanding 97
outliers 57
Output DEM 67
Output Line Spacing 14
OrthoEngine User’s Guide
output of DEM 67
Output Pixel Spacing 14
Output Projection 13
Overall Layout 54
overlap 52, 54, 64, 70, 73
Overlay 118
Overview 55
Overview (Chip Manager) 137
Overviews 129
P
Pack (Chip Manager) 140
Pan 122
Parity 46, 49, 61
PARITY(parity) 61
Pat-B 27
PAUSE(n) 60
PCIDSK 128
Perform Bundle Adjustment 59
Perform Merge (Chip Manager) 139
performing bundle adjustment 55
phi 27, 55
photo north 27
Photo Orientation 30
Photo Scale 23, 24
Pixel Sampling 74
Pixel Spacing 14, 80
place cursor 123
plot the distribution of GCPs 54
Point Mode 49, 61
point read 49
POINT(point mode) 61
points 65, 88
polarizing monitors and glasses
advantages and disadvantages 82
Polygon mask 76
Polygons 66, 89
PolyLine 75
Polynomial Math Model 7
minimum number of GCPs 35
153
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Starting a project 11
understanding solution 56
Polynomial Order 36, 38, 39, 41
polynomial transformations 8
POS/EO 27
position of sensor 55
position of the camera 27
position the aerial photographs 30
Preferences (Chip Manager) 141
Principal Point Offset 22, 24
Processing Start Time 30, 54
produce a report (Chip Manager) 140
Project Information
for Aerial Photography projects 9
for Mosaic Only project 12
for Polynomial projects 11
for Rational Functions projects 11
for Satellite Orbital projects 10
for Thin Plate Spline 12
project information report 132
Project Report 132
projection 12, 13
for 3-D feature extraction 86
puck 45
Q
Quick Open 18
Quick Open & Close 18
QUICKBIRD
DEM from stereo pairs 69
intro to OrthoEngine 1
joining tiles 126
minimum number of GCPs 34
stitching 126
supported formats 19
understanding Rational Functions Math Model 7
understanding Satellite Orbital Math Model 5
154
R
RADAR
supported formats 19
Radar Enhanced Frost 108
Radar Enhanced Lee 110
Radar Gamma Filter 107
Radar Kuan 109
RADARSAT
converting the DEM datum 126
DEM from stereo pairs 69
intro to OrthoEngine 1
minimum number of GCPs 34
RADARSAT Specific Model 10
SAR 19
selecting left and right images 70
setting the GCP elevation datum 128
supported formats 19
understanding Satellite Orbital Math Model 5
using Pixel Sampling 72
Web tool for selecting stereo pairs 69
Radial Distortion 22
radial distortion. See Principal Point Offset
Radial Lens Distortion 22, 24
Radian 28
Rapid Positioning Capability 7
Rational Functions Math Model 6
equations 7
minimum number of GCPs 34
Starting a project 11
understanding solution 56
Read CD-ROM 15
Read GCPs from Text File 49
Read Generic Image File 17
Read PCIDSK File 17
Read satellite images 15, 16, 17
Read Tape 16
Reapply Mosaicking 118
recompute model 132
rectangular sensor cells 24
reduce disk space used (Chip Manager) 140
PCI Geomatics
reducing eyestrain 82, 83
Re-enhance 121
reference frame 23, 47
reference frame for tablet 45
regenerating the mosaic 118
Region of Interest (ROI) 43
relating images together. See tie point
Reload 122
remove gaps in chip database 140
remove image from project 124
Rename Image 124
Rename images 124
replace elevation values under mask 76
replace pixel values 125
Reports (Chip Manager) 140
reprojecting DEM 79
reprojecting images 69
Resampling 64, 104
Residual Errors 56
Residual Report 58
editing points 59
resolution 14, 73
Resolution of DEM 67
Restore Defaults for chip search 43
RGB color bands 43
RGB color bands (Chip Manager) 137
RGB Mapper 123
Ridges (2D) 66
rigorous math model 5, 55
Orthorectification 98
ROI 43
Root 121
rotate images 29, 30
rotate kappa 27, 29
RPC 7
rules for format strings 60
S
Sampling Interval 102
SAR 19
OrthoEngine User’s Guide
minimum number of GCPs 34
SAR Type 16
Satellite Orbital Math Model 5
minimum number of GCPs 34
Starting a project 10
understanding solution 55
satellite sensors supported 1, 18
save a layer 93
save project as template 133
scale 23
Score Channel 72, 73
Search Criteria 41, 43
search for chips 42
Search image chips (Chip Manager) 139
search the chip database (Chip Manager) 139
select a 3-D stereo pair 84
select a GCP on a tablet 48
selected channels 16
Set Camera Calibration 24
set default units for datum 128
Set GCP Projection based on Output Projection 14
Set of DEMs to Merge 64
Set of Vector Layers to Interpolate 66
Set Trim % 121
set up tablet 46
setting GCP elevation units 127
shadows 52
Shapes. See masks
Shortcuts for the 3-D viewer 94
Show Distribution 44
Show Image or DEM 75
Show Mask 76
shutter glasses
advantages and disadvantages 82
simple math models 56
geometric correction 101
SIN 8 Pt and 16 Pt SinX/X 105
Size of DEM 67
size of DEM pixel 74
size of the chip 137, 138
155
-
size of the search area 45
SLASH 60
Smooth filter 78
Snap to Line 90
Snap to Vertex 90
solution for rigorous math models 55
source image for chip 136
SPACE 60
SPOT
DEM from stereo pairs 69
intro to OrthoEngine 1
joining tiles 126
minimum number of GCPs 34
stitching 126
supported formats 19
understanding Satellite Orbital Math Model 5
SPOTIMAGE SPOT 19
square sensor cells 24
Standard Aerial Camera 9
Start
Aerial Photography project 9
OrthoEngine 9
Polynomial project 11
project to mosaic existing orthos 12
Rational Functions project 11
Satellite Orbital project 10
Thin Plate Spline project 12
understanding project work flows 2
Start Orbit Calculation 17
Status Descriptions 103
stereo cursor
understanding 81
using 84
stereo pairs of images 69
stitching image tiles 126
Stop Bits 46, 49, 61
STOP(stop bits) 61
Strategies for editing DEMs 78
Stream Mode 49, 61
STREAM(stream mode) 61
156
strings of characters for tablets 48
subset chip database 139
Summary report (Chip Manager) 140
Super Structure IRS 18
Supported Satellite Formats 18
supported sensors 1
Supresoft 80, 131
Switch Stream Mode 61
SWITCH(switch stream mode) 61
Switching between Chip and Overview 137
Switching between image and DEM 75
switching to stereo cursor 85
Switch-stream Mode 49
Symbols 54
symmetric distortion. See Radial Lens Distortion
Sync Image/Photo 124
Sync Image/Photos 125
SYSTEMATIC geodetic processing 18
T
tablet
add or modify 48
ASCII mode 48
connect to 46
to collect GCPs 45, 47
Tablet Configuration 48, 60
tablet configurations 48
tablet definitions 61
Tablet Format Strings 60
Tablet Setup and Map Tie-down 46
TABLET(tablet number) 61
Tail Trim 121
Tape Format 16
template for project 133
text file containing coordinates for DEM 65
Thin Plate Spline Math Model 8
minimum number of GCPs 34
Starting a project 12
understanding solution 56
three-by-three pattern 52
PCI Geomatics
Three-dimension vectors. See 3-D Feature Extraction
Threshold values 132
tie point
change default color 131
choosing quality 52
collect tie point automatically 53
collect tie point manually 52
to generate DEM 64
understanding 51
Tie Point Distribution Pattern 54
TIFF 128
TIN 65
Tolerance 68
Toutin’s Model 10
TP Collection 53
Trace 75
Trace&Close 75
transformations
Polynomial 8
Thin Plate Spline 8
transmit
coordinate from tablet 49
Troubleshooting
orthorectified Images 104
the math model solution 56
U
undo vectors 90
Urban Areas 78
Use bounds and resolution 67
Use Grid Pinning 47
Use Image Chip 42
Use pixels/lines and bounds 67
Use pixels/lines and resolution 67
User Defined Filter 106
User Input 10, 27
USGS Digital Orthophoto Quads and Quarter Quads 64
Utilities
converting the DEM datum 126
remove image from project 124
OrthoEngine User’s Guide
rename image 124
replace pixel values 125
Stitch Image Tiles 126
Sync Images 125
Utilities (Chip Manager) 138, 139, 140
V
Valleys (2D) 66
Vector File 66
vectors
add lines 88
add points 88
add polygons 89
Attribute table 92, 93
change color 123
change priority of layers 87
delete a layer 94
delete line or polygon 92
delete vertex 91
editing tools 90
extracting lines from DEM 96
extracting points from DEM 95
import 122
import layers 87
insert vertex 91
metadata 92, 93
move vertex or point 92
save a layer 93
snap 90
to generate DEM 65, 67
undo 92
Video Camera 9
video camera calibration 21
view an image 17, 133
view image during DEM editing 75
view selected GCPs 44
view the coordinates 123
viewer (Chip Manager) 137
viewing geometry 55
visibility of layers 87
157
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W
work flow 2, 3
for 3-D feature extraction 83
Working Cache 30
working in 3-D 84
Y
Y Scale Factor 24
Z
Zoom
Zoom 1 to 1 Image Resolution 122
Zoom In 122
Zoom Interactive 122
Zoom Out 122
Zoom to Overview 122
158
PCI Geomatics
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