Lossless hyperspectral-image compression using context-based conditional average

Hongqiang Wang; S. Derin Babacan; Khalid Sayood

doi:10.1109/TGRS.2007.906085

Lossless hyperspectral-image compression using context-based conditional average

Hongqiang Wang, S. Derin Babacan, Khalid Sayood

Electrical & Computer Engineering

Research output: Contribution to journal › Article › peer-review

59 Scopus citations

Abstract

In this paper, a new algorithm for lossless compression of hyperspectral images is proposed. The spectral redundancy in hyperspectral images is exploited using a context-match method driven by the correlation between adjacent bands. This method is suitable for hyperspectral images in the band-sequential format. Moreover, this method compares favorably with the recent proposed lossless compression algorithms in terms of compression, with a lower complexity.

Original language	English (US)
Pages (from-to)	4187-4193
Number of pages	7
Journal	IEEE Transactions on Geoscience and Remote Sensing
Volume	45
Issue number	12
DOIs	https://doi.org/10.1109/TGRS.2007.906085
State	Published - Dec 2007

Keywords

Conditional average
Context coding
Correlation
Entropy code
Golomb-rice code
Hyperspectral image
Image coding

ASJC Scopus subject areas

Electrical and Electronic Engineering
Earth and Planetary Sciences(all)

Access to Document

10.1109/TGRS.2007.906085

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