Paper
31 July 2002 Compression of hyperspectral image based on three-dimensional SPIHT algorithm
Shanshan Yu, Yezhang Zhang
Author Affiliations +
Proceedings Volume 4875, Second International Conference on Image and Graphics; (2002) https://doi.org/10.1117/12.477125
Event: Second International Conference on Image and Graphics, 2002, Hefei, China
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.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shanshan Yu and Yezhang Zhang "Compression of hyperspectral image based on three-dimensional SPIHT algorithm", Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); https://doi.org/10.1117/12.477125
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Cited by 2 scholarly publications.
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KEYWORDS
Image compression

Wavelets

Hyperspectral imaging

Wavelet transforms

3D image processing

Quantization

Computer programming

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