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Proceedings Paper

Lossless compression of 3D ultraspectral sounder data using linear prediction with lattice coding
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Paper Abstract

Ultraspectral sounder data is known for its huge size and sensitivity to noise in retrieving geophysical parameters. Lossless compression of it is thus desired for archival and transfer purposes. In this paper, we propose a lossless compression scheme which consists of a linear prediction, a lattice encoder, and an entropy encoder. The linear prediction serves as a whitening tool to produce a normally distributed residual. The lattice encoder can use low bit rates to approximate a Gaussian source. The entropy encoder is then used for encoding the final residual whose variance is reduced by the lattice encoder. The compression on the standard ultraspectral test dataset set of 10 AIRS granules shows that the proposed scheme outperforms DPVQ, JPEG2000 and the common compression utility BZIP2.

Paper Details

Date Published: 26 August 2005
PDF: 7 pages
Proc. SPIE 5889, Satellite Data Compression, Communications, and Archiving, 588909 (26 August 2005); doi: 10.1117/12.618208
Show Author Affiliations
Shih-Chieh Wei, Tamkang Univ. (Taiwan)
Bormin Huang, CIMSS, Univ. of Wisconsin-Madison (United States)

Published in SPIE Proceedings Vol. 5889:
Satellite Data Compression, Communications, and Archiving
Bormin Huang; Roger W. Heymann; Charles C. Wang, Editor(s)

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