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Optical Engineering

Application Of Predictive Compression Methods To Synthetic Aperture Radar Imagery I
Author(s): Susan A.S. Werness
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Paper Abstract

Owing to the rapidly decaying autocorrelation function of synthetic aperture radar (SAR) imagery, predictive compression methods have not been widely used in image coding systems designed for SAR data. Because of the uncorrelated nature of SAR data, the prediction system design problem is approached in this paper from the point of view of statistics matching and decorrelation of reconstruction errors rather than minimization of the mean square error. It is demonstrated on 6 m resolution SAR magnitude data that a simple predictive coding system utilizing an unadaptive moving-average (MA) predictor and a Gaussian optimal quantizer can result in satisfactory reconstructed imagery at compression ratios of 2:1 to 4:1. Advantages of MA predictors are their lack of stability problems and their limited memory in the presence of channel errors.

Paper Details

Date Published: 1 December 1987
PDF: 10 pages
Opt. Eng. 26(12) 261200 doi: 10.1117/12.7977156
Published in: Optical Engineering Volume 26, Issue 12
Show Author Affiliations
Susan A.S. Werness, Environmental Research Institute of Michigan (United States)

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