研究了SAR图像目标特征增强的变分方法.通过分析P-M扩散方程中的扩散系数，得出梯度(Canny)边缘检测算子对SAR图像的非恒虚警性使得滤波后图像的边缘变得模糊.而ROA算子能有效地检测出图像中的边缘，但较难检测出图像中的强散射点目标.基于SAR幅度图像中相干斑噪声的Rayleigh分布，从最大后验概率估计出发，结合ROA边缘检测图像以及SAR幅度信息来构造扩散系数，建立SAR图像目标特征增强的变分模型.实测SAR图像处理结果显示该方法在充分抑制均匀区域的相干斑噪声的同时能较好地保护并增强图像的边缘和强散射区域.

A variation approach for SAR image feature enhancement is proposed. By analyzing the diffusion coefficient of P-M diffusion, it was found that it is the non-CFAR character of Canny detector that blurs the edges in the filtered SAR image. Further more, the ROA detector can detect edges in the image, but it lacks the ability of detecting the strong scatters. Based on the Rayleigh distribution of speckle in the amplitude image, the variation model for feature enhancement was established by combining the ROA detected version and the amplitude of SAR image from the MAP estimator. Experiments on the real SAR image demonstrated that the proposed method can suppress speckle efficiently in the homogeneous areas and preserve or even enhance edges and strong targets in the image.