SAR干涉图中的斑点噪声是对相位解缠的极大障碍，为了得到更精确的地形模型，必须在相位解缠前对干涉图进行斑点噪声滤波。提出了一种干涉图的小波域多尺度滤波算法。对干涉图的实部和虚部分别进行处理，用Pearson分布系确定了信号和噪声项小波系数的概率密度函数，然后用最大后验概率（Maximum A Posterior,MAP)准则估计无噪数据的小波系数。将本算法和另外3种滤波算法进行比较。结果表明，本滤波算法对SAR干涉图有很强的噪声抑制能力，并能保持干涉图的相位细节信息和相位分布。

Strong speckle noise of SAR interferogram is a great obstacle to phase unwrapping. In order to obtain a more accurate topographic model, a noise filtering step must be performed before the unwrapping of phase. In this article, we propose to filter this noise with a multi-resolution analysis of the interferogram, the real part and the imaginary part of the interferogram are processed seperatively. Several different probability density function are modeled with the Pearson system of distributions, then the wavelet coefficients of the noiseless data are estimated with a Bayesian model, maximizing the posteriori probability density function. The result is compared to that of three other methods and shows that the proposed method is powerful to interferogram speckle noise reduction, as well as it can preserve fine details in the interferogram that are directly related to the ground topography and maintain phase values distribution.