基于非下采样Shearlet和方向权值邻域窗的非局部均值SAR图像相干斑抑制

非局部均值算法将传统的图像去噪算法由局部计算模型推广到非局部计算模型，取得了良好的效果.但对于合成孔径雷达图像，使用观测值和各向同性邻域窗来度量相似性，缺乏鲁棒性和方向性，不利于捕获图像边缘结构信息.提出了基于非下采样Shearlet特征描述子和方向权值邻域窗的非局部均值算法.实验表明,该算法不但有效地去除了相干斑，而且很好地保持了图像的几何结构信息，为后期SAR图像的理解与解译奠定了良好的基础.

SAR image despeckling: based on non-local means with non-subsample Shearlet and directional windows

Good performance has been obtained by extending traditional image denoising algorithm from local computation model to non-local one with non-local means algorithm. For synthesis aperture radar (SAR) image, however, the similarity measured by observations and isotropic window is not robust and without direction, which is bad for capturing the structure of image. In this paper, Non-subsample Shearlet feature and directional neighborhood based non-local means algorithm are proposed. Experimental results demonstrated that the improved non-local means algorithm can not only remove the speckle, but also preserve the geometrical structure information which is essential for understanding and interpretation of SAR image.