Translator Disclaimer
Paper
5 December 2001 Relative error-constrained compression for synthetic aperture radar data
Author Affiliations +
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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bruno Aiazzi, Luciano Alparone, and Stefano Baronti "Relative error-constrained compression for synthetic aperture radar data", Proc. SPIE 4475, Mathematics of Data/Image Coding, Compression, and Encryption IV, with Applications, (5 December 2001); https://doi.org/10.1117/12.449575
PROCEEDINGS
12 PAGES


SHARE
Advertisement
Advertisement
Back to Top