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Proceedings Paper

High compression of SAR imagery for battlefield surveillance
Author(s): Nasser M. Nasrabadi; Joseph P. Sattler; Heesung Kwon; Syed A. Rizvi
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Paper Abstract

In this paper a compression algorithm is developed to compress SAR imagery at very low bit rate. A new vector quantization (VQ) technique called the predictive residual vector quantizer (PRVQ) is presented for encoding the SAR imagery. Also a variable-rate VQ scheme called the entropy- constrained PRVQ (EC-PRVQ), which is designed by imposing a constraint on the output entropy of the PRVQ, is designed. Experimental results are presented for both PRVQ and EC-PRVQ at high compression ratios. The encoded images are also compared with that of a wavelet-based coder.

Paper Details

Date Published: 10 June 1996
PDF: 12 pages
Proc. SPIE 2757, Algorithms for Synthetic Aperture Radar Imagery III, (10 June 1996); doi: 10.1117/12.242052
Show Author Affiliations
Nasser M. Nasrabadi, SUNY/Buffalo (United States)
Joseph P. Sattler, Army Research Lab. (United States)
Heesung Kwon, SUNY/Buffalo (United States)
Syed A. Rizvi, SUNY/Buffalo (United States)


Published in SPIE Proceedings Vol. 2757:
Algorithms for Synthetic Aperture Radar Imagery III
Edmund G. Zelnio; Robert J. Douglass, Editor(s)

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