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中文摘要：
将Contourlet变换用于SAR图像的统计特性研究中．基于Contourlet域隐马尔可夫树模型（CHMT），从图像复原的角度出发，结合最小均方误差估计和Bayes估计给出一种SAR图像相干斑抑制的新方法．并给出基于拉普拉斯金字塔算法（LP）分解的斑点方差估计方法．实验中与小波域HMT算法进行了比较，本文方法在方向信息的保留和斑点的抑制上均有明显改进．
英文摘要：
Contourlet transform was introduced in the SAR image statistical property research work. Based on Contourlet domain Hidden Markov Trees Model, starting from image restore methods, a novel SAR image despeckling method was given. This method combined the SAR image despeckling technology with minimum mean square error （MMSE） and Bayes estimate. A new speckle variation estimate method was given based on Laplacian pyramid （LP）. The results comparison with wavelet domain method were given. Experimental results show that the method represents better performance in speckle reduction and edges information detection.
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