由于雷达回波的相干性，合成孔径雷达（SAR）图象上存在着斑点噪声，因此，为消除这种噪声，提出了一种基于静态小波分解的硬阈值滤波方法，该方法首先将SAR图象分解至静态小波域，然后在静态小波域中将噪声的小波系数收缩至零，将此算法应用于ERS－1 SAR图象斑点噪声滤波，并与基于Mallat分解的滤波算法和另外3种典型的SAR图象滤波算法进行比较，结果表明，该方法不仅可以有效地去除斑点噪声,并且可以保持SAR图象的精细纹理结构。

Synthetic aperture radar(SAR) images are disturbed by a speckle noise depending on the signal(the ground reflectivity) due to the radar wave coherence. Images have a strong variability from one pixel to another reducing essentially the efficiency of the algorithms of object detection and classification. In this study, we propose to suppress this noise with a multiresolution analysis of the image. Because the Mallat decomposition can not preserve the translation invariance of an image, the filter in this paper is based on stationary wavelet decomposition. This method is used to an ERS-1 SAR image and then it is compared to a filter based on Mallat decomposition and three other classic SAR image filters, the results show that the presented approach has the advantage both in speckle suppression and the preservation of image details.