A satellite imaging chain based on the Compressed Sensing technique

Mikael Carlavan 1, * Laure Blanc-Féraud 1 Marc Antonini 2 Carole Thiebaut 3 Christophe Latry 3 Yves Bobichon 4
* Corresponding author
1 MORPHEME - Morphologie et Images
CRISAM - Inria Sophia Antipolis - Méditerranée , IBV - Institut de Biologie Valrose : U1091, Laboratoire I3S - SIS - Signal, Images et Systèmes
Abstract : Satellite imaging has been the focus of intense works in remote sensing for the last years. The ability of satellite optical systems to produce high-resolution images has indeed been of a great interest in applications such as change detection or image classification. The design of a satellite acquisition chain is however quite challenging as it involves expensive processes such as sampling and coding. In this work, we investigate the performances of a low-resource satellite imaging chain based on the Compressed Sensing (CS) acquisition technique. We propose a reconstruction algorithm which takes into account the degradations of the satellite imaging chain and we present results on a real satellite data.
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Mikael Carlavan, Laure Blanc-Féraud, Marc Antonini, Carole Thiebaut, Christophe Latry, et al.. A satellite imaging chain based on the Compressed Sensing technique. On-Board Payload Data Compression Workshop, Oct 2012, Barcelone, Spain. ⟨hal-00748523⟩

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