合成孔径雷达（SAR）图像存在较强的相干斑点噪声，严重地影响了地物信息的提取与SAR图像的应用效果。提出了一种新的SAR图像斑点噪声滤波算法，该算法以一种基于膜模型的Markov随机场的近似最优迭代滤波算法(TSPR)为基础，考虑了邻域空间关系对势能函数的影响，并通过在迭代过程中自适应修正惩罚系数，来达到更好的斑点噪声滤波效果。通过对含不同强度斑点噪声的退化图像的对比试验结果来看，该算法在提高处理后图像的信噪比方面，能够取得较TSPR算法更佳的效果。

Speckle noise is serious in SAR (synthetic aperture radar) image. It will greatly affect the information extraction of terra and object and the application of SAR image. A novel filtering algorithm for speckle noise in SAR image is presented here. This algorithm is based on an iterative filter that based on a membrane model Markov random field approximation optimized by a synchronous local iterative method (TSPR). With this algorithm, the affect of the energy function by neighbors’ spatial relation is taken into account. Through self adaptive correcting the penalty coefficient in iteration process better filtering effect can be acquired. According the comparison experiments about faded images caused by speckle noise of various intensities, with the algorithm presented here we can restore the image with higher Signal Noise Ratio (SNR) than TSPR algorithm.