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) |
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Pages (from-to) | 4187-4193 |
Number of pages | 7 |
Journal | IEEE Transactions on Geoscience and Remote Sensing |
Volume | 45 |
Issue number | 12 |
DOIs | |
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)