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提出了一种抑制ＳＡＲ图像相干斑噪声和提取弱反射地物边缘方法．传统噪声抑制和小波变换去噪方法有其不足之处，本文将小波变换和维纳滤波结合抑制ＳＡＲ图像相干斑噪声，通过选择恰当小波基获得良好滤波效果。采用最小错误准则计算ＳＡＲ图像的理论分割阈值，通过逐次迭代得到其合理大小，利用形态算子作用于分割图像获得其边缘．实际ＳＡＲ图像测试结果表明了本文方法的有效性．
A method of suppressing the speckle noise of SAR images and extracting the edges of weak reflection objects is proposed. Traditional noise suppression and wavelet transform denoising methods have their disadvantages. In this paper, the wavelet transform and Wiener filter are combined to suppress the speckle noise of SAR image, and the good filtering effect is obtained by selecting the proper wavelet base. The minimum segmentation criterion is used to calculate the theoretical segmentation threshold of SAR image. The reasonable size of the SAR image is obtained by successive iterations, and the morphological operator is used to obtain the edge of the segmentation image. The actual SAR image test results show the effectiveness of the proposed method.