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.

Abrardo, A., Barni, M., Bertoli, A., Garzelli, A., Magli, E., Nencini, F., et al. (2008). Low-complexity and error-resilient hyperspectral image compression based on distributed source coding. In Proc. SPIE 7109 (pp.7109V). SPIE [10.1117/12.799990].

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

ABRARDO, ANDREA;BARNI, MAURO;GARZELLI, ANDREA;
2008-01-01

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.
2008
9780819473400
Abrardo, A., Barni, M., Bertoli, A., Garzelli, A., Magli, E., Nencini, F., et al. (2008). Low-complexity and error-resilient hyperspectral image compression based on distributed source coding. In Proc. SPIE 7109 (pp.7109V). SPIE [10.1117/12.799990].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/3319
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