Merging Multiresolution SPOT HRV and Landsat TM Data

Merging Multiresolution SPOT HRV and Landsat TM Data
Image Processing Brief
Merging Multiresolution SPOT HRV and
Landsat TM Data
R. Welch and Manfred Ehlers
Laboratory for Remote Sensing and Mapping Science, Department of Geography, University of Georgia, Athens, GA 30602
ROCEDURES for merging multisensor and multiresolution
satellite data in digital formats to create composite images
of enhanced interpretability have been discussed by Welch (1984)
and Chavez (1984). With the successful launch of SPOT-l in February, 1986, and the acquisition of 20-m resolution multispectral
and lO-m resolution panchromatic images with the High Resolution Visible (HRV) solid state line array cameras, attention
has focused on the possibilities for using digital image processing techniques to sharpen the multispectral image by integrating or merging it with the panchromatic band (Welch, 1985).
Similarly, there is considerable interest in merging the SPOT-l
lO-m panchromatic band with Landsat-4 and -5 Thematic Mapper (TM) images of 28.5-m pixel resolution to create multisensor,
multiresolution, multispectral, and multitemporal composite
image products that can be effectively analyzed by visual interpretation. This brief documents methodologies that have proved
successful and provides examples of composite images that
demonstrate the improvements in interpretability achieved by
merging image data sets of high and low resolution.
In order to evaluate merged multiresolution data sets, it is
desirable to utilize imagery of an urban area where the rendition
of buildings, land parcels, edges, and other high frequency detail can be used for comparative assessments of image quality
(Welch, 1982). Consequently, a 5-km by 5-km test site located
in the city of Atlanta, Georgia and recorded by the Landsat-5
TM on 4 April 1985 and by the SPOT HRV on 4 May 1986 was
selected for this study (Figures 1 to 3, Table 1).
The Landsat-5 TM data were available in computer compatible
tape (CCT-pt) formats, and had been resampled to 28.5-m pixel
resolution and corrected for radiometric and geometric distortions by the Thematic Mapper Image Processing System (TIPS).
Earlier studies have shown the Landsat-5 TM data to be of exceptionally good geometric fidelity (Borgeson et aI., 1985; Welch
et al., 1985).
The SPOT data were recorded with the HRV camera pointing
17 degrees off-axis, resulting in effective instantaneous fieldsof-view of about 11 m and 22 m for the panchromatic and multispectral modes, respectively. These data were processed at Level
18 by SPOT Image Corporation to yield an equivalent vertical
image resampled to nominal pixel dimensions of 10 m (panchromatic) and 20 m (multispectral). However, as is the case for
all SPOT-l images, the multispectral and panchromatic data are
not co-registered. Registration must be undertaken by the user
if a merged image product is required.
A 512 by 512 pixel subset of the SPOT-l 10-m panchromatic
data was selected as the reference image to which the SPOT-l
and Landsat-5 TM multispectral images could be registered. A
screen-sized subarea of this reference image is presented in Figure 3. Urban details, including roads, buildings, and parks, are
easily identified.
Vol. 53, No.3, March 1987, pp. 301-303.
A general procedure for creating data sets that will be in
register involves the following steps: (1) determination of the
image coordinates of control points common to all data sets; (2)
computation of the unknown coefficients for a first degree polynomial equation required to register the multispectral images
to the panchromatic reference image; and (3) resampling of the
multispectral data sets to 10-m resolution using parametric cubic
interpolation techniques to avoid blocky image structures
(Schowengerdt et aI., 1984). These steps were employed to create resampled 512 by 512 image data files of lO-m resolution for
the SPOT-l multispectral bands (bands 1 to 3) and the six visible,
near-infrared, and short wavelength infrared TM bands (bands
1 to 5 and 7).
Registration accuracy was evaluated at withheld test points,
and yielded root-mean-square error (RMSE) values of approximately ± 7 m and ± 14 m for the SPOT-l and TM multispectral
images, respectively. These values are equivalent to ± 0.4 data
pixel for the SPOT-l and ±0.5 data pixel for the Landsat-5 image
subsets, and indicate the excellent geometric integrity of the
satellite image data. Errors of this magnitude are not apparent
in the composite images (Figures 4 to 6).
Once a layered set of images is stored on disk, the digital
numbers (ON) associated with the various multispectral images
may be combined or merged with those for the panchromatic
reference image using techniques previously discussed by Saint
and Weill (1984), Cliche et al., (1985), and Chavez (1986). These
methods may be summarized in the two following equations:
M,' = ai * (M, * P)'/2 + h,
M,' = ai * (w,M, + w 2 P) + h,
where M,' is the ON for a pixel in the ith band of the merged
image; M; is the ON for the corresponding pixel of the ith multispectral image; P is the ON for the corresponding panchromatic reference image pixel; w, and W 2 are weighting factors;
and ai and h, are scaling factors to place the resulting ON within
the dynamic range (0,255). By using either of these algorithms,
the panchromatic image 0 s are merged or integrated with the
ONs for the resampled multispectral images to create sharpened
images that can be contrast-stretched using histogram equalization or similar digital image enhancement techniques. The
sharpened, contrast-stretched images may then be displayed as
a red-green-blue false color composite on the CRT display of the
image processing system or written to film for hardcopy products.
The above algorithms were applied with reasonable success
in merging both the SPOT-l and Landsat TM multispectral data
with the SPOT-l 10-m panchromatic reference image. However,
images of superior contrast and spectral discrimination were
achieved using a third method based on the intensity-hue-saturation (iHS) color transformation procedures documented by
Haydn et al. (1982). This technique was recently employed by
Hallada (ASPRS, 1986) to merge Landsat and SPOT images of
©1987 American Society for Photogrammetry
and Remote Sensing
FIG. 1. False color Landsat-5 TM image of Atlanta, Georgia recorded in
April 1985 (band 2 = blue, band 3 = green, band 4 = red). Image pixel
size is 28.5 m.
FIG. 4. False color composite image of the merged multi resolution SPOTpanchromatic and multispectral bands. Image pixel size is 10m. The
spatial and spectral resolution properties of the SPOT-1 data are retained
in the merged image.
FIG. 2. False color SPOT-1 image of Atlanta, Georgia recorded in May
1986 (band XS1 = blue, band XS2 = green, band XS3 = red). Image
pixel size is 20 m.
FIG. 5. False color composite image of the Landsat-5 TM, bands 2, 3, and
4, and the SPOT-1 panchromatic band. Image pixel size is 10m. The
interpretability of this multisensor, multi resolution, multispectral, multitemporal image is comparable to the merged SPOT-1 image in Figure 4.
FIG. 3. SPOT-1 panchromatic reference image of Atlanta, Georgia. At 10m resolution, only one-fourth the area of Figure 2 is displayed.
FIG. 6. False color composite image of the Landsat-5 TM infrared bands
(bands 4, 5, and 7) and the SPOT-1 panchromatic band. Image pixel size
is 10 m. This merged image display indicates that the SPOT-1 panchromatic band can be successfully used to enhance the interpretability of
the Landsat TM infrared bands.
Landsat-5 TM
Recording Date
Interval (fl.m)
Pixel (m)
the Chernobyl reactor site for the cover of the October 1986
issue of Photogrammetric Engineering and Remote Sensing.
With the IHS method, three selected bands of the registered
SPOT HRV and Landsat TM multispectral data are first transformed into the IHS domain. The SPOT panchromatric reference
image DNs are then substituted for the DNs of the intensity
component, and the data are transformed back to the red-greenblue (RGB) color domain. The resulting composite SPOT and SPOTTM images shown in Figures 4 to 6 are of similar spatial resolution to the panchromatic reference image, yet provide excellent spectral discrimination of natural and cultural features in
the urban environment.
Striking improvements in the quality of SPOT-l and Landsat5 TM multispectral images of 20-m and 28.5-m pixel resolution
can be realized by using an IHS algorithm to merge the individual multispectral bands with a SPOT-1 panchromatic reference
image of 10-m resolution. The resulting false color composites
have spatial resolution properties similar to those of the reference panchromatic image, yet retain the spectral discrimination
qualities of the original multispectral data set. Thus, it is entirely
feasible to establish layered digital image data bases from which
either true or false color multisensor, multiresolution, multitemporal images of enhanced quality can be generated by digital
image processing techniques. Such products will prove useful
to scientists seeking to maximize the amount of information
extracted from satellite image data, to photogrammetrists faced
with the revision of outdated maps of developing countries,
and to cartographers involved in the preparation of image maps
of optimum quality.
SPOT image data are copyrighted ((c) 1986) by the Centre
National d'Etudes Spatiales, Toulouse, France, and distributed
in the United States by SPOT Image Corporation, Reston, Virginia.
American Society for Photogrammetry and Remote Sensing, 1986. Cover
Photo, Photogmnl/netric Engineering and Remote Sensing, Vol. 52, o.
Borgeson, W.T., R.M. Batson, and H.H. Kieffer, 1985. Geometric Accuracy of Landsat-4 and Landsat-5 Thematic Mapper Images. Photogrammetric Engineering and Remote Sellsing, Vol. 51, No. 12, pp.
Chavez, P.S., Jr., 1984. Digital Processing Techniques for Image Mapping with Landsat TM and SPOT Simulator Data, Proceedings of the
XVlllth International Symposium on Remote Sensing of Environment,
Paris, France, pp. 101-116.
- - , 1986. Digital Merging of Landsat TM and Digitized NHAP Data
for 1:24,000-Scale Image Mapping, Photogrammetric Engineering and
Remote Sensing, Vol. 52, No. 10, pp. 1637-1646.
Cliche, G., F. Bonn, and P. Teillet, 1985. Integration of the SPOT Panchromatic Channel into Its Multispectral Mode for Image Sharpness
Enhancement, Photogramlnetric Engineering and Remote Sensing, Vol.
51, No.3, pp. 311-316.
Haydn, R., G.W. Dalke, J. Henkel, and J.E. Bare, 1982. Application of
the IHS Color Transform to the Processing of Multisensor Data and
Image Enhancement, Proceedings of the International Symposium on
Remote Sensing of Arid and Semi-Arid Lands, Cairo, Egypt, pp. 599616.
Saint, G., and G. Weill, 1984. SPOT Simulation Methodology: Simulated vs. Satellite Image Parameters, SPOT Simulation Applications
Handbook, American Society of Photogrammetry, Falls Church, Virginia, pp. 19-28.
Schowengerdt, R., S. Park, and R. Gray, 1984. Topics in Two-Dimensional Sampling and Reconstructions of Images, International Journal
of Remote Sensing, Vol. 5, No.2, pp. 333---347.
Welch, R., 1982. Spatial Resolution Requirements for Urban Studies.
International Journal of Remote Sensing, Vol. 3, No.2, pp. 139-146.
- - , 1984. Merging Landsat and SIR-A Image Data in Digital Formats, Imaging Technology in Research and Development, July 1984, pp.
- - , 1985. Cartographic Potential of SPOT Image Data, Photogmmmetric Engineering and Remote Sensing, Vol. 51, No.8, pp. 1085-1091.
Welch, R., T.R. Jordan, and M. Ehlers, 1985. Comparative Evaluations
of the Geodetic Accuracy and Cartographic Potential of Landsat-4
and Landsat-5 Thematic Mapper Image Data, Photogrnmmetric Engineering and RWlOte Sensing, Vol. 51, No.9, pp. 1249-1262.
(Accepted 19 December 1986)
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