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Proceedings Paper

Use of independent component analysis for lossless compression of ultraspectral sounder data
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Paper Abstract

Independent component analysis has been known for its success in blind source separation. It features a decorrelation capability beyond second-order moments. Recently ICA has been used in lossy compression for target detection in hyperspectral imager data where loss of unimportant features does not affect the detection result. For the ultraspectral sounder data, it is better to be lossless compressed for the ill-posed retrieval of geophysical parameters. In this paper we will try to use ICA in the lossless compression of ultraspectral sounder data. The compression result shows that ICA compares favorably with JPEG2000, JPEG-LS, and CCSDS IDC 5/3 on the ten standard AIRS granules dataset.

Paper Details

Date Published: 1 October 2007
PDF: 6 pages
Proc. SPIE 6683, Satellite Data Compression, Communications, and Archiving III, 668309 (1 October 2007); doi: 10.1117/12.737606
Show Author Affiliations
Shih-Chieh Wei, Tamkang Univ. (Taiwan)
Bormin Huang, Univ. of Wisconsin, Madison (United States)

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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