Classified Vector Quantiztion on Wavelet Image with 

Directional Tree Structure Vector Combination

Zheng Yong; Li De-Ming; Zhu Wei-le

Volume 27 Issue 12

Dec. 2005

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Article Navigation > Journal of Electronics & Information Technology > 2005 > 27(12): 1959-1963

Zheng Yong, Li De-Ming, Zhu Wei-le. Classified Vector Quantiztion on Wavelet Image with Directional Tree Structure Vector Combination[J]. Journal of Electronics & Information Technology, 2005, 27(12): 1959-1963.

Citation:

Zheng Yong, Li De-Ming, Zhu Wei-le. Classified Vector Quantiztion on Wavelet Image with Directional Tree Structure Vector Combination[J]. Journal of Electronics & Information Technology, 2005, 27(12): 1959-1963.

Citation:

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Classified Vector Quantiztion on Wavelet Image with Directional Tree Structure Vector Combination

Received Date: 2004-06-29
Rev Recd Date: 2005-06-15
Publish Date: 2005-12-19

Abstract

Abstract

A new method to perform classified vector quantization on wavelet images using directional tree structure vector combination is proposed. It makes vector combination by employing the direction character of subband coefficients and the correlation between and within subbands. It has two steps of classification with the vectors energy and activity and thus reduces the inner dispersion of the classified vectors. The classified information needs few bits to carry. The weighted mean square error rule using human visual characteristics is used to improve quantization gain. Simulation results show its coding efficiency for wavelet images.

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References

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