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Proceedings Paper

CNES studies of on-board compression for multispectral and hyperspectral images
Author(s): Carole Thiebaut; Emmanuel Christophe; Dimitri Lebedeff; Christophe Latry
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Paper Abstract

Future high resolution instruments planned by CNES for space remote sensing missions will lead to higher bit rates because of the increase in resolution, dynamic range and number of spectral channels for multispectral (up to 16 bands) and hyperspectral (hundreds of bands) imagery. Lossy data compression is then needed, with compression ratio goals always higher and with low-complexity algorithm. For optimum compression performance of such data, algorithms must exploit both spectral and spatial correlation. In the case of multispectral images, CNES (in cooperation with Thales Alenia Space, hereafter TAS) studies have led to an algorithm using a fixed transform to decorrelate the spectral bands, the CCSDS codec compresses each decorrelated band using a suitable multispectral rate allocation procedure. This low-complexity decorrelator is adapted to hardware implementation on-board satellite and is under development. In the case of hyperspectral images, CNES (in cooperation with TAS/TeSA/ONERA) studies have led to a full wavelet compression system followed by zerotree coding methods adapted to this decomposition. We are investigating other preprocessors such as Independent Component Analysis which could be used in both approaches. CNES also participates to the new CCSDS Multispectral and Hyperspectral Data Compression Working Group.

Paper Details

Date Published: 19 September 2007
PDF: 15 pages
Proc. SPIE 6683, Satellite Data Compression, Communications, and Archiving III, 668305 (19 September 2007); doi: 10.1117/12.734186
Show Author Affiliations
Carole Thiebaut, CNES (France)
Emmanuel Christophe, CNES (France)
Dimitri Lebedeff, Thales Alenia Space (France)
Christophe Latry, CNES (France)

Published in SPIE Proceedings Vol. 6683:
Satellite Data Compression, Communications, and Archiving III
Roger W. Heymann; Bormin Huang; Irina Gladkova, Editor(s)

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