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Journal of Electronic Imaging

Class-prioritized compression of multispectral imagery data
Author(s): John A. Saghri; Andrew G. Tescher; Mohamed J. Omran
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Paper Abstract

A joint classification-compression scheme that provides the user with added capability to prioritize classes of interest in the compression process is proposed. The dual compression system includes a primary unit for conventional coding of a multispectral image set followed by an auxiliary unit to code the resulting error induced on pixel vectors that represent classes of interest. This technique effectively allows classes of interest in the scene to be coded at a relatively higher level of precision than nonessential classes. Prioritized classes are selected from a thematic map or directly specified by their unique spectral signatures. Using the specified spectral signatures of the prioritized classes as end members, a modified linear spectral unmixing procedure is applied to the original data as well as to the decoded data. The resulting two sets of concentration maps, which represent classes prioritized before and after compression, are compared and the differences between them are coded via an auxiliary compression unit and transmitted to the receiver along with a conventionally coded image set. At the receiver, the differences found are blended back into the decoded data for enhanced restoration of the prioritized classes. The utility of this approach is that it works with any multispectral compression scheme. This method has been applied to test the imagery from various platforms including NOAA’s AVHRR (1.1 km GSD), and LANDSAT 5 TM (30 m GSD), LANDSAT 5 MSS (79 m GSD).

Paper Details

Date Published: 1 April 2002
PDF: 11 pages
J. Electron. Imaging. 11(2) doi: 10.1117/1.1455008
Published in: Journal of Electronic Imaging Volume 11, Issue 2
Show Author Affiliations
John A. Saghri, California Polytechnic State Univ. (United States)
Andrew G. Tescher, Compression Science, Inc. (United States)
Mohamed J. Omran, Kuwait Univ. (Kuwait)


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