非下采样Contourlet HMT模型

非下采样Contourlet变换（NSCT）不仅具有类似传统小波变换和Contourlet变换的多尺度和多方向特性，而且还具有良好的平移不变特性．文中对NSCT变换系数进行研究，获得NSCT变换的方向子带系数同样具有持续性和聚集性的结论；在此基础上结合隐Markov树模型，建立了一种新的基于NSCT域的隐Markov树模型NSCT—HMT，并且给出了该模型的参数结构以及模型参数的训练方法；最后将所提出的模型应用于图像去噪中取得了很好的仿真效果．

The nonsubsampled Contourlet HMT model

The non-subsampled Contourlet transform （NSCT） has not only characteristics of nmlti-scale, multi- direction and anisotropy, like traditional wavelet transform and Contourlet transform, but also the good charac- teristics of shift-invariant. We draw the conclusion that the directional subband coefficients also have persistence and aggregation through studying the coefficients of the NSCT. On tile basis of HMT. we establish a novel non-subsampled Contourlet transform domain hidden Markov tree model, NSCT-HMT. and give the parameters structure of the model as well as the training method of the model parameters. Finally, we apply the proposed model to image denoising, and achieve a good simulation effect.