The selection of an efficient speckle filter for SAR imagery primarily depends upon a specific application of interest and statistical characteristics of the noise present in SAR datasets. The main goal of this study is to assess the performance of the two wavelet shrinkage-based filtering techniques (VISU shrink and SURE shrink) against two spatial adaptive filters (Enhanced Lee and Gamma MAP) and one non-local filter (NL-SAR) for the removal of speckle noise from high-resolution COSMO-SkyMed (CSK) SAR datasets. Before applying these filters to real CSK datasets, they are tested on synthetically generated speckled test datasets and benchmark simulated SAR datasets. Experimental analysis has been conducted on synthetically generated speckled datasets based on varying level of speckle noise introduced on test images. In case of benchmark datasets, numerous qualitative and quantitative measures are observed and evaluated. To find the best filter for real CSK data, a Pareto optimality concept has been used where the coefficient of variation is the parameter considered. From the findings, it is evident that VISU shrink-generated speckle filtering solution is non-dominated by all the other filtering solutions except NL-SAR-based speckle suppression in smooth areas. Considering the various user-defined situations of homogeneity and heterogeneity in the SAR scene, an overall performance index is formulated and VISU shrink performs the best in all user-defined conditions.

用于SAR图像的高效散斑滤波器的选择主要取决于感兴趣的特定应用和SAR数据集中存在的噪声的统计特性。这项研究的主要目的是针对两种空间自适应滤波器（Enhanced Lee和Gamma MAP）和一个非局部滤波器（NL-SAR）评估两种基于小波收缩的滤波技术（VISU收缩和SURE收缩）的性能。用于从高分辨率COSMO-SkyMed（CSK）SAR数据集中去除斑点噪声。在将这些过滤器应用于实际的CSK数据集之前，先对它们进行综合生成的斑点测试数据集和基准模拟SAR数据集进行测试。基于在测试图像上引入的不同水平的斑点噪声，已经对合成生成的斑点数据集进行了实验分析。对于基准数据集，观察和评估了许多定性和定量措施。为了找到用于真实CSK数据的最佳滤波器，已经使用了帕累托最优概念，其中变异系数是所考虑的参数。从发现中可以明显看出，除了平滑区域中基于NL-SAR的斑点抑制以外，VISU收缩生成的斑点过滤解决方案不受其他所有过滤解决方案的支配。考虑到SAR场景中用户定义的同质性和异质性的各种情况，制定了总体性能指标，VISU收缩在所有用户定义的条件下均表现最佳。从发现中可以明显看出，除了平滑区域中基于NL-SAR的斑点抑制以外，VISU收缩生成的斑点过滤解决方案不受其他所有过滤解决方案的支配。考虑到SAR场景中用户定义的同质性和异质性的各种情况，制定了总体性能指标，VISU收缩在所有用户定义的条件下均表现最佳。从发现中可以明显看出，除了平滑区域中基于NL-SAR的斑点抑制以外，VISU收缩生成的斑点过滤解决方案不受其他所有过滤解决方案的支配。考虑到SAR场景中用户定义的同质性和异质性的各种情况，制定了总体性能指标，VISU收缩在所有用户定义的条件下均表现最佳。