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Proceedings Paper

Compression of hyperspectral image based on three-dimensional SPIHT algorithm
Author(s): Shanshan Yu; Yezhang Zhang
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Paper Abstract

In response to the high data volumes of hyperspectral images and high data rates required for their transmission, many hyperspectral data compression methods have been researched in recent years . In this paper, a new compression algorithm for hyperspectral image is proposed, which pays much more attention to its peculiarity of much higher spectral resolution. The new method combines three-dimensional integer wavelet transform and vector quantization, as well as Said and Pearlman's SPIHT algorithm is extended to three dimensions. The principle ofthe new method can be explained in three steps. First, three-dimensional integer wavelet transform is performed on the hyperspectral image. Second, spectral vectors are formed on the basis of the orientation features of three-dimensional wavelet coefficients, thus the high spectral dependencies of hyperspectral image can be exploited simultaneously with wavelet tree structure. Third, an algorithm that extends SPIHT algorithm to three dimensions is used to encode the spectral vectors. In order to test the effectiveness of the proposed algorithm, 32 bands of an AVIRIS image are used for computer simulation. The results show that the SNR in the reconstructed images can reach more than 40 dB on average at 0.6 bit per pixel, which indicates the proposed algorithmis efficient for the compression of hyperspectral images.

Paper Details

Date Published: 31 July 2002
PDF: 6 pages
Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); doi: 10.1117/12.477125
Show Author Affiliations
Shanshan Yu, Harbin Institute of Technology (China)
Yezhang Zhang, Harbin Institute of Technology (United States)

Published in SPIE Proceedings Vol. 4875:
Second International Conference on Image and Graphics
Wei Sui, Editor(s)

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