适用于高分辨SAR图像的全局稳态最小水平集分割方法  

A Global Stationary Minimum Level Set Segmentation Method for High-resolution SAR Images

作　　者：冯籍澜[1] 曹宗杰[1] 皮亦鸣[1] 

机构地区：[1]电子科技大学电子工程学院,成都611731

出　　处：《电子与信息学报》2010年第11期2618-2623,共6页Journal of Electronics & Information Technology

基　　金：国家自然科学基金(60802065;60772143)资助课题

摘　　要：该文针对高分辨率SAR图像的分割问题提出了一种新的快速的水平集方法。该方法基于G0分布能够同时描述高分辨率和中低分辨率条件下的SAR图像统计特性,通过水平集方法求解能量泛函最小化实现SAR图像的分割。由于能量泛函被设计为具有全局稳态最小值,使得该方法具有较好的全局分割能力和比较快的分割速度,从而增强了该方法的实用性。利用模拟和真实SAR图像上的分割实验验证了该方法的有效性。A new and fast level set method for segmentation of high-resolution SAR images into statistical homogenous areas is proposed.This approach is based on the G0 statistical model which can describe high-resolution SAR images as well as low-resolution SAR images.And the segmentation is obtained by minimizing energy function with level set methods.As the energy functional is designed to have global stationary minimum,a global and fast segmentation technique can be obtained,thus the practicality of the proposed approach is enhanced.The performance of the algorithm is verified with experiments based on both synthetic and real SAR images.

关 键 词：SAR图像处理 变分水平集方法 全局稳态最小 G0分布 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]