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基于小波域統(tǒng)計(jì)混合模型的圖像降噪方法

易翔 王蔚然

易翔, 王蔚然. 基于小波域統(tǒng)計(jì)混合模型的圖像降噪方法[J]. 電子與信息學(xué)報(bào), 2005, 27(11): 1722-1725.
引用本文: 易翔, 王蔚然. 基于小波域統(tǒng)計(jì)混合模型的圖像降噪方法[J]. 電子與信息學(xué)報(bào), 2005, 27(11): 1722-1725.
Yi Xiang, Wang Wei-ran. Method of Image Denoising Based on Statistical Mixture Model in Wavelet Domain[J]. Journal of Electronics & Information Technology, 2005, 27(11): 1722-1725.
Citation: Yi Xiang, Wang Wei-ran. Method of Image Denoising Based on Statistical Mixture Model in Wavelet Domain[J]. Journal of Electronics & Information Technology, 2005, 27(11): 1722-1725.

基于小波域統(tǒng)計(jì)混合模型的圖像降噪方法

Method of Image Denoising Based on Statistical Mixture Model in Wavelet Domain

  • 摘要: 該文提出了一種基于小波域統(tǒng)計(jì)混合模型的圖像降噪方法。該方法首先利用尺度間模型,將小波系數(shù)分成兩類:有意義系數(shù)和無意義系數(shù);然后在小波域同層模型中運(yùn)用最大后驗(yàn)概率估計(jì)方法,從有意義系數(shù)中恢復(fù)出原始系數(shù)。文章給出了算法的完整步驟。實(shí)驗(yàn)結(jié)果及分析表明了該方法的有效性。
  • Chang S, Yu B, Vetterli M. Adaptive wavelet thresholding for image denoising and compression[J].IEEE Trans. on Image Processing.2000, 9(9):1532-1546[2]Crouse M S, Nowak R D. Wavelet-based signal processing using hidden Markov models[J].IEEE Trans. on Signal Processing.1998, 46(4):886-902[3]Lewis A S, Knowles G. Image compressing using the 2-d wavelet transform. IEEE Trans. on Image Processing, 1992, 1(2): 224-250.[4]Liu J, Moulin P. Information-theoretic analysis of interscale and intrascale dependencies between image wavelet coefficients[J].IEEE Trans. on Image Processing.2001, 10(11):1647-1658[5]Simoncelli E P, Adelson E H. Noise removal via Bayesian wavelet coring. In Proc. IEEE Int. Conf. on Image Processing, Lausanne, Switzerland, 1996, 1: 379-382.[6]Donoho D L, Johnstone I M. Ideal spatial adaptation via wavelet shrinkage[J].Biometrika.1994, 81(3):425-455[7]Donoho D L, Johnstone I M. Adapting to unknown smoothness[8]via wavelet shrinkage. Journal of American Statistical Assoc., 1995, 90(432): 1200-1224.[9]Rombery J K.[J].Choi H, Baraniuk R G. Hidden Markov tree modeling of complex wavelet transforms. In Proc. IEEE ICASSP 00, Istanbul, Turkey.2000,:-[10]Kingsbury N G. The dual-tree complex wavelet transform: a new efficient tool for image restoration and enhancement. In Proc. EUSIPCO 98, Island of Rhodes, Greek, 1998: 319-322.[11]Kingsbury N G. A dual-tree complex wavelet transform with improved orthogonality and symmetry properties. In Proc. IEEE Int. Conf. on Image Processing, Vancouver, Canada, 2000, 2: 375-378.[12]Sendur I, Selesnick I W. Bivariate shrinkage function for wavelet-based denoising exploiting interscale dependency[J].IEEE Trans. on Signal Processing.2002, 50(11):2744-2756
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出版歷程
  • 收稿日期:  2004-04-28
  • 修回日期:  2004-12-30
  • 刊出日期:  2005-11-19

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