Archivio Istituzionale della RicercaIn remote sensing systems, on-board data compression is a crucial task that has to be carried out with limited computational resources. In this paper we propose a novel lossless compression scheme for multispectral and hyperspectral images, which combines low encoding complexity and high-performance. The encoder is based on distributed source coding concepts, and employs Slepian-Wolf coding of the bitplanes of the CALIC prediction errors to achieve improved performance. Experimental results on AVIRIS data show that the proposed scheme exhibits performance similar to CALIC, and significantly better than JPEG 2000.
Improved low-complexity intraband lossless compression of hyperspectral images by means of Slepian-Wolf coding / A., Nonnis; M., Grangetto; Magli, Enrico; Olmo, Gabriella; M., Barni. - (2005), pp. 829-832. (Intervento presentato al convegno ICIP 2005 - IEEE International Conference on Image Processing) [10.1109/ICIP.2005.1529879].
Improved low-complexity intraband lossless compression of hyperspectral images by means of Slepian-Wolf coding
MAGLI, ENRICO;OLMO, Gabriella;
2005
Abstract
In remote sensing systems, on-board data compression is a crucial task that has to be carried out with limited computational resources. In this paper we propose a novel lossless compression scheme for multispectral and hyperspectral images, which combines low encoding complexity and high-performance. The encoder is based on distributed source coding concepts, and employs Slepian-Wolf coding of the bitplanes of the CALIC prediction errors to achieve improved performance. Experimental results on AVIRIS data show that the proposed scheme exhibits performance similar to CALIC, and significantly better than JPEG 2000.
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https://hdl.handle.net/11583/1413228
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