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Statistical Image Modeling In The Contourlet Domain Using Contextual Hidden Markov Models

机译:使用上下文隐马尔可夫模型的Contourlet域中的统计图像建模

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摘要

In this paper, a contourlet contextual hidden Markov model (C-CHMM) is established for modeling contourlet images by adapting a previous CHMM for wavelet images (W-CHMM). A mutual information based context design procedure is presented, through which a new context has been constructed. The C-CHMM is tested in a denoising application with promising results, which verifies its effectiveness. This new model is demonstrated to be a better model for contourlet images than the state of the art contourlet hidden Markov tree model. As a general image model, it also shows more potential than the baseline W-CHMM.
机译:在本文中,建立了轮廓波上下文隐式马尔可夫模型(C-CHMM),以通过将先前的CHMM适应小波图像(W-CHMM)来建模轮廓波图像。提出了一种基于互信息的上下文设计程序,通过该程序可以构造新的上下文。 C-CHMM在去噪应用中进行了测试,结果令人满意,证明了其有效性。与最新的Contourlet隐藏Markov树模型相比,该新模型被证明是Contourlet图像更好的模型。作为一般图像模型,它还显示出比基线W-CHMM更大的潜力。

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