Paper
26 August 2005 Lossless compression of 3D ultraspectral sounder data using linear prediction with lattice coding
Author Affiliations +
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.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shih-Chieh Wei and Bormin Huang "Lossless compression of 3D ultraspectral sounder data using linear prediction with lattice coding", Proc. SPIE 5889, Satellite Data Compression, Communications, and Archiving, 588909 (26 August 2005); https://doi.org/10.1117/12.618208
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Computer programming

Quantization

Infrared radiation

JPEG2000

Data compression

Optical spheres

Infrared imaging

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