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Proceedings Paper

Hyperspectral image compression using 3D discrete cosine transform and entropy-constrained trellis-coded quantization
Author(s): Glen P. Abousleman; Michael W. Marcellin; Bobby R. Hunt
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Paper Abstract

A system is presented for compression of hyperspectral imagery which utilizes trellis coded quantization (TCQ). Specifically, TCQ is used to encode transform coefficients resulting from the application of an 8X8X8 discrete cosine transform. Side information and rate allocation strategies are discussed. Entropy-constrained codebooks are designed using a modified version of the generalized Lloyd algorithm. This entropy constrained system achieves a compression ratio of greater than 70:1 with an average PSNR of the coded hyperspectral sequence exceeding 40.5 dB.

Paper Details

Date Published: 8 July 1994
PDF: 12 pages
Proc. SPIE 2231, Algorithms for Multispectral and Hyperspectral Imagery, (8 July 1994); doi: 10.1117/12.179774
Show Author Affiliations
Glen P. Abousleman, Univ. of Arizona (United States)
Michael W. Marcellin, Univ. of Arizona (United States)
Bobby R. Hunt, Univ. of Arizona (United States)

Published in SPIE Proceedings Vol. 2231:
Algorithms for Multispectral and Hyperspectral Imagery
A. Evan Iverson, Editor(s)

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