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Proceedings Paper

New algorithm for lossless hyper-spectral image compression with mixing transform to eliminate redundancy
Author(s): ChengJun Xie; Lin Xu
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Paper Abstract

This paper presents a new algorithm based on mixing transform to eliminate redundancy, SHIRCT and subtraction mixing transform is used to eliminate spectral redundancy, 2D-CDF(2,2)DWT to eliminate spatial redundancy, This transform has priority in hardware realization convenience, since it can be fully implemented by add and shift operation. Its redundancy elimination effect is better than (1D+2D)CDF(2,2)DWT. Here improved SPIHT+CABAC mixing compression coding algorithm is used to implement compression coding. The experiment results show that in lossless image compression applications the effect of this method is a little better than the result acquired using (1D+2D)CDF(2,2)DWT+improved SPIHT+CABAC, still it is much better than the results acquired by JPEG-LS, WinZip, ARJ, DPCM, the research achievements of a research team of Chinese Academy of Sciences, NMST and MST. Using hyper-spectral image Canal of American JPL laboratory as the data set for lossless compression test, on the average the compression ratio of this algorithm exceeds the above algorithms by 42%,37%,35%,30%,16%,13%,11% respectively.

Paper Details

Date Published: 5 March 2008
PDF: 9 pages
Proc. SPIE 6623, International Symposium on Photoelectronic Detection and Imaging 2007: Image Processing, 66231U (5 March 2008); doi: 10.1117/12.791529
Show Author Affiliations
ChengJun Xie, Beihua Univ. (China)
Lin Xu, Beihua Univ. (China)


Published in SPIE Proceedings Vol. 6623:
International Symposium on Photoelectronic Detection and Imaging 2007: Image Processing

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