一种SAR图像分割新方法

合成孔径雷达（SAR）图像中固有的相干斑噪声，严重影响了图像分割算法性能。为了改善SAR图像分割质量，本文提出了一种联合PM扩散模型和各向异性MRF模型的图像分割方法。首先对传统PM扩散模型的扩散系数进行简化和近似，限制模型的解的唯一；然后使用改进后的模型对原始SAR图像进行非线性扩散，在抑制噪声的同时保持图像结构细节；继而，通过在标记场势能函数中引入观测数据灰度信息，将经典的基团势能改进为基于灰度加权的各向异性势能，提高边缘像素和图像奇异点的分割准确率。实验表明，本文算法的分割结果区域连通性更好，边缘轮廓分割更精细。

A novel method for SAR image segmentation

Speckle noise that is inherent in SAR imagery makes the traditional image segmentation methods inefficient.To improve the performance,a novel method combining PM diffusion model and the anisotropic MRF model is proposed in this paper.First,to restrict the uniqueness of the solution,the traditional PM diffusion model is simplified using mathematic approximation.Then the modified diffusion model is employed to smooth the speckle noise of SAR image.Second,the filtered image is segmented using MRF model-based method, in which the original intensity information is introduced into the computation of potential function, i.e.,the clique potential is weighted by local difference of intensity values,thus the anisotropic potential is achieved.Experimental results on real SAR imagery demonstrate that the proposed method segment the image more uniformly and the contour position is more exact than the traditional method.