融合Ratio边缘信息的水平集SAR图像分割方法

提出了一种融合边缘和区域信息的变分水平集合成孔径雷达图像分割方法.该方法不需要去除相干斑噪声的预处理过程,利用具有恒虚警特性的Ratio算子提取合成孔径雷达图像的边缘信息,并与无边缘活动轮廓模型结合建立合成孔径雷达图像分割能量泛函模型,通过最小化能量泛函得到曲线演化偏微分方程,采用变分水平集方法求解演化方程,实现了合成孔径雷达图像的分割.分别采用模拟和真实合成孔径雷达图像对该方法进行了验证,实验结果表明,该方法实现了合成孔径雷达图像中目标与背景的正确分割,具有较好的边缘定位能力.

Level set SAR image segmentation method combined with ratio edge information

A variational level set synthetic aperture radar (SAR) image segmentation method based on edge and region information is proposed. An energy functional adapted for SAR image segmentation is defined, which consists of an active contour without the edge model and the edge information of SAR image by the Ratio operator with CFAR. Partial differential equations (PDE) of curve evolution are obtained by minimization of the energy functional. To implement image segmentation, the solution of the PDEs by a variational level set approach is applied. The performance of the method is verified by both synthetic and real SAR images. It is shown that the method can accurately extract targets from the SAR image but without any despeckle step, which possesses a preferable edge accuracy.