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Proceedings Paper

Practical issues for transform coding of multispectral imagery
Author(s): John A. Saghri; Andrew G. Tescher; John T. Reagan
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Paper Abstract

An overview of a robust and implementable compression algorithm previously developed for multispectral imagery is given. This three-dimensional terrain-adaptive transform-based algorithm involves a one dimensional Karhunen-Loeve (KLT) transform followed by two- dimensional discrete cosine transform. The images are spectrally decorrelated via the KLT to produce the eigen images. The resulting spectrally-decorrelated eigen images are then compressed using the JPEG algorithm. The key feature of this approach is that it incorporates the best methods available to fully exploit the spectral and spatial correlation in the data. The novelty of this technique lies in its unique capability to adaptively vary the characteristics of the spectral decorrelation transformation based upon variations in the local terrain. In addition several relevant practical issues are addressed. These issues include: (1) Handling the panchromatic sharpening band, (2) tradeoff between spectral and spatial fidelity, (3) different grouping of bands for spectral decorrelation, (4) impact of band misalignment on performance, (5) impact of dead and saturated pixels on performance, and (6) impact of preprocessing on performance.

Paper Details

Date Published: 17 November 1995
PDF: 12 pages
Proc. SPIE 2587, Geographic Information Systems, Photogrammetry, and Geological/Geophysical Remote Sensing, (17 November 1995); doi: 10.1117/12.226812
Show Author Affiliations
John A. Saghri, Kuwait Univ. (United States)
Andrew G. Tescher, Lockheed Palo Alto Research Lab. (United States)
John T. Reagan, Lockheed Palo Alto Research Lab. (United States)

Published in SPIE Proceedings Vol. 2587:
Geographic Information Systems, Photogrammetry, and Geological/Geophysical Remote Sensing
Joan B. Lurie; James J. Pearson; Eugenio Zilioli, Editor(s)

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