一种规整化的各向异性扩散相干斑抑制算法

针对基于各向异性扩散的相干斑抑制算法 (SRAD)中存在的不合理性 ,即算法在均匀区域内降噪特性一般 ,并且扩散系数的非凸可能导致解不收敛到正确的图像 ,从理论上进行了系统的分析和论证 ,并依据保持图像细节的规整化准则 ,构造出新的扩散控制系数 .在此基础上 ,进一步提出了一种更合理的规整化各向异性扩散模型 (RSRAD) ,该模型可以有效地克服SRAD中存在的不合理性 .实验结果表明 ,RSRAD算法优于SRAD .

A Regularized Anisotropic Diffusion for Speckle Reducing

Speckle reducing anisotropic diffusion (SRAD) algorithm still has disadvantages. Firstly, the diffusion coefficient is not a convex function, which leads to an unstable solution. At the second point, SRAD is anisotropy even in the homogeneous areas, this will depress the ability of reducing speckle. In this paper we systematically analyze the problem mentioned above and propose a new diffusion coefficient based on the edge-preserving regularization method. We also construct a new anisotropic diffusion module, R-SRAD, which is more reasonable. The experimental results show that our R-SRAD is more effective in comparison with the SRAD.