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采用方向樹結(jié)構(gòu)矢量組合的小波圖像分類矢量量化

鄭勇,  李德明,  朱維樂

鄭勇, 李德明, 朱維樂. 采用方向樹結(jié)構(gòu)矢量組合的小波圖像分類矢量量化[J]. 電子與信息學(xué)報(bào), 2005, 27(12): 1959-1963.
引用本文: 鄭勇, 李德明, 朱維樂. 采用方向樹結(jié)構(gòu)矢量組合的小波圖像分類矢量量化[J]. 電子與信息學(xué)報(bào), 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.

采用方向樹結(jié)構(gòu)矢量組合的小波圖像分類矢量量化

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

  • 摘要: 該文提出了采用方向樹結(jié)構(gòu)矢量組合對(duì)小波圖像進(jìn)行分類矢量量化的新方法。該方法的矢量構(gòu)成結(jié)合了子帶系數(shù)的方向性，充分利用了子帶系數(shù)的帶間和帶內(nèi)的相關(guān)性，按能量和活躍度進(jìn)行兩級(jí)分類，降低了類中矢量的內(nèi)部離散度，分類信息占用比特?cái)?shù)少，并采用了基于人眼視覺特性的加權(quán)均方誤差準(zhǔn)則進(jìn)行矢量量化，提高了量化增益。仿真結(jié)果表明，該方法實(shí)現(xiàn)簡(jiǎn)單，可以達(dá)到很好的壓縮效果。
    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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  • Mallat S. Multifrequency channel decomposition of images and wavelet models[J].IEEE Trans. on ASSP.1989, 37 (12):2091-2110[2]Atonini M, Barlaud M, Mathieu P. Image coding using wavelet transform, IEEE Trans[J].on Image Processing.1992, 1(2):205-220[3]Zaid A O, Olivier C, Marmotton F. Wavelet image coding with adaptive dead-zone selection: application to JPEG2000. Image Processing. 2002. Proceedings, 2002, 3(1): 253-256.[4]ISO/IEC, International Standard 15444-1: 2000, Information technology-JPEG2000 image coding system-Part 1: Core coding system.[5]Shapiro J M. Embeded image coding using zerotrees of wavelet coefficients[J].IEEE Trans. on Signal Processing.1993, 41(12):3445-3462[6]Cosman P C, Gray R M, Vetterli M. Vector quantization of image subbands: A survey[J].IEEE Trans. on Image Processing.1996, 5(2):202-225[7]Taekon K, Seungkeun C, Van Dyck R E, Bose N K, Chandler A. Classified zerotree wavelet image coding and adaptive packetization for low-bit-rate transport. IEEE Trans. on CSVT, 2001, 11(9): 1022-1034.[8]Desarte P, Macq B, Slock D. Signal-adapted multiresolution transform for image coding[J].IEEE Trans. on Information Theory.1992, 38(2):897-904[9]Huh Y, Hwang J J, Rao K R. Block wavelet transform coding of images using classified vector quantization. IEEE Trans. on CSVT, 1996, 5(1): 63-67.[10]Villasenor J, Belzer B, Liao J. Wavelet filter evaluation for image[11]compression. IEEE Trans[J].on Image Processing.1995, 4(8):1053-1060
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出版歷程
  • 收稿日期:  2004-06-29
  • 修回日期:  2005-06-15
  • 刊出日期:  2005-12-19

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