Low-complexity and error-resilient hyperspectral image compression based on distributed source coding

A. Abrardo; M. Barni; A. Bertoli; A. Garzelli; E. Magli; F. Nencini; B. Penna; R. Vitulli

doi:10.1117/12.799990

10 October 2008 Low-complexity and error-resilient hyperspectral image compression based on distributed source coding

A. Abrardo, M. Barni, A. Bertoli, A. Garzelli, E. Magli, F. Nencini, B. Penna, R. Vitulli

Proceedings Volume 7109, Image and Signal Processing for Remote Sensing XIV; 71090V (2008) https://doi.org/10.1117/12.799990
Event: SPIE Remote Sensing, 2008, Cardiff, Wales, United Kingdom

Abstract

In this paper we propose a lossless compression algorithm for hyperspectral images based on distributed source coding; this algorithm represents a significant improvement over our prior work on the same topic, and has been developed during a project funded by ESA-ESTEC. In particular, the algorithm achieves good compression performance with very low complexity; moreover, it also features a very good degree of error resilience. These features are obtained taking inspiration from distributed source coding, and particularly employing coset codes and CRC-based decoding. As the CRC can be used to decode blocks using a reference different from that used to compress the image, this yields error resilience. In particular, if a block is lost, decoding using the closest collocated block in the second previous band is successful about 70% of the times.

Citation Download Citation

A. Abrardo, M. Barni, A. Bertoli, A. Garzelli, E. Magli, F. Nencini, B. Penna, and R. Vitulli "Low-complexity and error-resilient hyperspectral image compression based on distributed source coding", Proc. SPIE 7109, Image and Signal Processing for Remote Sensing XIV, 71090V (10 October 2008); https://doi.org/10.1117/12.799990

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