Lossless hyperspectral image compression using context-based conditional averages

Hongqiang Wang, S. Denn Babacan, Khalid Sayood

Research output: Contribution to journalConference articlepeer-review

17 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)418-426
Number of pages9
JournalData Compression Conference Proceedings
StatePublished - 2005
EventDCC 2005: Data Compression Conference - Snowbird, UT, United States
Duration: Mar 29 2005Mar 31 2005

ASJC Scopus subject areas

  • Computer Networks and Communications


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