Compressed sensing based compression of SAR raw data

G. Rilling, Michael Davies, Bernie Mulgrew

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Due to their noise-like features, SAR images are difficult to acquire with compressed sensing techniques. However, some parts of the images, typically associated to man-made structures, are compressible and we investigate two techniques exploiting that information to allow a compressive acquisition of the whole image. These techniques result in a significant enhancement of the image quality compared to classical compressed sensing. Moreover, compared to classical sampling and quantisation of the SAR raw data, they allow a significant reduction of
bitrate with a limited increase of the distortion. However, their efficiency
depends strongly on the presence of compressible parts in the image.
Original languageEnglish
Title of host publicationSPARS'09 - Signal Processing with Adaptive Sparse Structured Representations (2009)
Publication statusPublished - Apr 2009


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