基于混合迭代滤波的SAR图像相干斑抑制

该文将变窗Lee滤波与自蛇扩散结合，提出了一种抑制SAR图像相干斑噪声的混合迭代滤波新算法，并给出了SAR图像噪声方差的一种有效估计方法。该算法首先估计SAR图像局部统计参量，进而通过改进的变窗Lee滤波对SAR图像进行平滑去噪，接着利用自蛇扩散去除Lee滤波难以平滑的孤立点噪声与边缘噪声。在Lee滤波与自蛇扩散的混合迭代中，Lee滤波的窗尺度随迭代次数的增加而增大，从而在保护SAR图像边缘细节的同时，同质区得到更好平滑。实验结果表明，与已有多种抑斑算法相比，该文算法在SAR图像抑斑与边缘保护方面均获得了更好的性能。

SAR Image Despeckling Based on Mixed Iteration Filtering

A novel mixed iteration filtering algorithm is presented to reduce speckle noise in SAR image by combining the Lee filter with variable-size windows and self-snake diffusion,and an effect method to estimate noise’s variance of SAR image is given.Local statistical parameters of SAR image is first estimated,and then SAR image is smoothed by improved Lee filter with variable-size windows.Then self-snake diffusion is used to remove the remaining isolated points noise and edge noise in the image smoothed by Lee filter.The window size of Lee filter will be increased with the number of mixed iteration,and thus homogeneous regions of SAR image are smoothed better while image edge is protected.The experimental results show that,compared with several kinds of despeckling algorithms,the proposed algorithm has better performance in speckle suppression and edge protection.