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Proceedings Paper

Perceptual image compression for data transmission on the battlefield
Author(s): Jose Gerado Gonzalez; Mark J. T. Smith; Ingo Hontsch; Lina J. Karam; Kameswara Rao Namuduri; Harold H. Szu
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Paper Abstract

This paper treats the compression of Synthetic Aperture Radar (SAR) imagery. SAR images are difficult to compress, relative to natural images, because SAR contains an inherent high frequency speckle. Today's state-of-the-art coders are designed to work with natural images, which have a lower frequency content. Thus, their performance on SAR is under par. In this paper we given an overview performance report on the popular compressions techniques, and investigate three approaches to improve the quality of SAR compression at low- bit rates. First, we look at the design of optimal quantizers which we obtain by training on SAR data. Second, we explore the use of perceptual properties of the human visual system to improve subjective coding quality. Third, we consider the use of a model that separates the SAR image into structural and textural components. The paper concludes with a subjective evaluation of the algorithms based on the CCIR recommendation for the assessment of picture quality.

Paper Details

Date Published: 6 July 1998
PDF: 12 pages
Proc. SPIE 3387, Visual Information Processing VII, (6 July 1998); doi: 10.1117/12.316432
Show Author Affiliations
Jose Gerado Gonzalez, Georgia Institute of Technology (United States)
Mark J. T. Smith, Georgia Institute of Technology (United States)
Ingo Hontsch, Arizona State Univ. (United States)
Lina J. Karam, Arizona State Univ. (United States)
Kameswara Rao Namuduri, Clark-Atlanta Univ. (United States)
Harold H. Szu, Naval Surface Warfare Ctr. (United States)


Published in SPIE Proceedings Vol. 3387:
Visual Information Processing VII
Stephen K. Park; Richard D. Juday, Editor(s)

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