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Proceedings Paper

Relative error-constrained compression for synthetic aperture radar data
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Paper Abstract

Near-lossless compression, i.e., yielding strictly bounded reconstruction error, is extended to preserve the radiometric resolution of data produced by coherent imaging systems, like Synthetic Aperture Radar (SAR). First a causal spatial DPCM based on a fuzzy matching-pursuit (FMP) prediction is adjusted to yield a relative-error bounded compression by applying a logarithmic quantization to the ratio of original to predicted pixel values. Then, a noncausal DPCM is achieved based on the Rational Laplacian Pyramid (RLP), recently introduced by the authors for despeckling. The baseband icon of the RLP is (causally) DPCM encoded, the intermediate layers are uniformly quantized, and the bottom layer is logarithmically quantized. As a consequence, the relative error, i.e., pixel ratio of original to decoded image, can be strictly bounded around unity by the quantization step size of the bottom layer of the RLP. Experimental results reported on true SAR data from NASA/JPL AIRSAR show that virtually lossless images can be achieved with compression ratios larger than three.

Paper Details

Date Published: 5 December 2001
PDF: 12 pages
Proc. SPIE 4475, Mathematics of Data/Image Coding, Compression, and Encryption IV, with Applications, (5 December 2001); doi: 10.1117/12.449575
Show Author Affiliations
Bruno Aiazzi, Istituto di Ricerca sulle Onde Elettromagnetiche (Italy)
Luciano Alparone, Univ. degli Studi di Firenze (Italy)
Stefano Baronti, Istituto di Ricerca sulle Onde Elettromagnetiche (Italy)

Published in SPIE Proceedings Vol. 4475:
Mathematics of Data/Image Coding, Compression, and Encryption IV, with Applications
Mark S. Schmalz, Editor(s)

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