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Lossless hyperspectral image compression using context-based conditional averages

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3 Author(s)
Hongqiang Wang ; Dept. of Electr. Eng., Nebraska Univ., Lincoln, NE, USA ; S. D. Babacan ; K. Sayood

In this paper, we propose a compression algorithm focused on the peculiarities of hyperspectral images. The spectral redundancy in hyperspectral images is exploited by using a context matching method driven by the correlation between adjacent bands of hyperspectral spectral images. The method compares favorably with recent proposed lossless compression algorithms in terms of compression, with significantly lower complexity.

Published in:

Data Compression Conference

Date of Conference:

29-31 March 2005