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Proceedings Paper

A new interferential multispectral image compression algorithm based on adaptive classification and curve-fitting
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Paper Abstract

A novel compression algorithm for interferential multispectral images based on adaptive classification and curve-fitting is proposed. The image is first partitioned adaptively into major-interference region and minor-interference region. Different approximating functions are then constructed for two kinds of regions respectively. For the major interference region, some typical interferential curves are selected to predict other curves. These typical curves are then processed by curve-fitting method. For the minor interference region, the data of each interferential curve are independently approximated. Finally the approximating errors of two regions are entropy coded. The experimental results show that, compared with JPEG2000, the proposed algorithm not only decreases the average output bit-rate by about 0.2 bit/pixel for lossless compression, but also improves the reconstructed images and reduces the spectral distortion greatly, especially at high bit-rate for lossy compression.

Paper Details

Date Published: 5 September 2008
PDF: 9 pages
Proc. SPIE 7084, Satellite Data Compression, Communication, and Processing IV, 70840E (5 September 2008); doi: 10.1117/12.794332
Show Author Affiliations
Ke-Yan Wang, Xidian Univ. (China)
Yun-Song Li, Xidian Univ. (China)
Kai Liu, Xidian Univ. (China)
Cheng-Ke Wu, Xidian Univ. (China)

Published in SPIE Proceedings Vol. 7084:
Satellite Data Compression, Communication, and Processing IV
Bormin Huang; Roger W. Heymann; Joan Serra-Sagristà, Editor(s)

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