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Proceedings Paper

Variable-rate multistage vector quantization of multispectral imagery with greedy bit allocation
Author(s): Smita Gupta; Allen Gersho
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Paper Abstract

Multispectral satellite images of the earth consist of sets of images obtained by sensing electromagnetic radiation in different spectral bands for each geographical region. We have applied a variable rate multistage vector quantizer for the compression of multispectral imagery. Spectral and spatial correlation are simultaneously exploited by forming vectors from 3-dimensional data blocks. The wide variation in entropy across the data set is efficiently exploited by an adaptive bit allocation algorithm based on a greedy approach where the rate- distortion trade-off is locally optimized for each successive encoding stage. Simulation results on an image set acquired by a Thematic Mapper scanner are presented. A substantial improvement is obtained over prior vector quantization based coders for multispectral data compression.

Paper Details

Date Published: 22 October 1993
PDF: 12 pages
Proc. SPIE 2094, Visual Communications and Image Processing '93, (22 October 1993); doi: 10.1117/12.158006
Show Author Affiliations
Smita Gupta, Univ. of California/Santa Barbara (United States)
Allen Gersho, Univ. of California/Santa Barbara (United States)

Published in SPIE Proceedings Vol. 2094:
Visual Communications and Image Processing '93
Barry G. Haskell; Hsueh-Ming Hang, Editor(s)

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