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Proceedings Paper

Multicomponent compression with the latest CCSDS recommendation
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Paper Abstract

For optimum compression performances of multispectral and hyperspectral images, algorithms must exploit both spectral and spatial correlation of the data. To do this, different approaches are possible: a spectral decorrelation preprocessing stage followed by application of an image compressor to the decorrelated bands or, an integrated solution dealing with the three dimensions simultaneously. For example, Part II of JPEG2000 standard introduces a multi-component transform capability applied prior Part I spatial wavelet decomposition and coding. This article proposes to use the CCSDS Image Data Compression Recommendation together with a spectral transform to perform a multicomponent compression. Depending on the number of spectral bands, an efficient spectral transform, such as the DCT, is applied first and the CCSDS algorithm encodes each decorrelated bands. We compare the performances of such a scheme with JPEG2000 and also with a comparable scheme with a very simple decorrelation stage. Thanks to a bit plane coding of blocks of wavelet coefficients, the CCSDS encoder is a good tool to control the quality or the rate of these transformed bands. We present performances for different types of sensors: multispectral and hyperspectral. This work is part of the CNES contribution to the new CCSDS Multispectral and Hyperspectral Data Compression Working Group.

Paper Details

Date Published: 31 August 2009
PDF: 11 pages
Proc. SPIE 7455, Satellite Data Compression, Communication, and Processing V, 745503 (31 August 2009); doi: 10.1117/12.825291
Show Author Affiliations
Carole Thiebaut, CNES (France)
Roberto Camarero, CNES (France)

Published in SPIE Proceedings Vol. 7455:
Satellite Data Compression, Communication, and Processing V
Bormin Huang; Antonio J. Plaza; Raffaele Vitulli, Editor(s)

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