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Lossless Hyperspectral-Image Compression Using Context-Based Conditional Average

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3 Author(s)
Hongqiang Wang ; Nebraska-Lincoln Univ., Lincoln ; S. Derin Babacan ; Khalid Sayood

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.

Published in:

IEEE Transactions on Geoscience and Remote Sensing  (Volume:45 ,  Issue: 12 )