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Proceedings Paper

Hyperspectral image lossless compression algorithm based on adaptive band regrouping
Author(s): Mingyi He; Lin Bai; Yuchao Dai; Jing Zhang
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Paper Abstract

Hyperspectral image has weak spatial correlation and strong spectral correlation. As to exploit spectrum redundancy sufficiently, it must be pre-processed. In this paper, a new algorithm for lossless compression of hyperspectral images based on adaptive band regrouping is proposed. Firstly, the affinity propagation clustering algorithm (AP) is chosen for band regrouping according to interband correlation. Then a linear prediction algorithm based on context prediction is applied to the hyperspectral images in different groups. Finally, the experimental results show that the proposed algorithm achieves performance gains of 1.12bpp over the conventional algorithm.

Paper Details

Date Published: 31 August 2009
PDF: 6 pages
Proc. SPIE 7455, Satellite Data Compression, Communication, and Processing V, 745504 (31 August 2009); doi: 10.1117/12.827450
Show Author Affiliations
Mingyi He, Northwestern Polytechnical Univ. (China)
Lin Bai, Northwestern Polytechnical Univ. (China)
Yuchao Dai, Northwestern Polytechnical Univ. (China)
Jing Zhang, Northwestern Polytechnical Univ. (China)

Published in SPIE Proceedings Vol. 7455:
Satellite Data Compression, Communication, and Processing V
Bormin Huang; Antonio J. Plaza; Raffaele Vitulli, Editor(s)

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