基于双变量模型和非下采样Contourlet变换的SAR图像相干斑抑制

SAR Image Despeckling Based on Bivariate Threshold Function in NSCT Domain

该文根据非下采样Contourlet分解系数与其父系数之间的相关性,给出非高斯双变量分布模型,应用贝叶斯估值理论推导得到该模型相应的非线性双变量阈值函数。综合SAR图像非对数加性模型和双变量阈值函数,提出基于双变量模型的非下采样Contourlet变换域SAR图像相干斑抑制方法(SNSCTBI)。实验通过对幅度格式和强度格式的SAR图像做相干斑抑制,结果表明该文算法很好地保持了原始图像的辐射特性,有效抑制了同质区域的相干斑,同时边缘等纹理信息保持清晰。

Considering the dependencies between the coefficients of Contourlet transform and their parents＇ coefficients,a non-Gaussian bivariate distribution is given,and corresponding nonlinear threshold function is derived from the model using Bayesian estimation theory.Combined nonlogarithmic additive model of SAR image with bivariate threshold function,a novel SAR image despeckling based on bivariate threshold function in Non-Subsampled Contourlet Transform domain（NSCT） is proposed.Experimental results for speckle reduction on amplitude and intensity of SAR images demonstrate that the method holds a good ability of radiometric preservation,the speckle is despeckled well in homogeneous regions,edges and textures of despeckled image are also clear.