场景语义SAR图像桥梁检测算法  

Detecting water bridge in SAR images via a scene semantic algorithm

作　　者：黄勇[1,2] 刘芳 HUANGYong;LIU Fang(School of Computer Science and Technology,Xidian Univ.,Xi5an 710071,China;Ministry of EducationKey Lab.of Intelligent Perception and Image Understanding,Xidian Univ.,Xi’an 710071,China)

机构地区：[1]西安电子科技大学计算机学院,陕西西安710071 [2]西安电子科技大学智能感知与图像理解教育部重点实验室,陕西西安710071

出　　处：《西安电子科技大学学报》2018年第4期40-44,共5页Journal of Xidian University

基　　金：国家重点基础研究发展计划资助项目(2013CB329402);国家自然科学基金资助项目(61573267);重大研究计划资助项目(91438201;91438103)

摘　　要：在合成孔径雷达图像中存在大量相干斑乘性噪声,导致桥梁检测中极易出现漏检和误检.针对这一问题提出了基于场景语义的水上桥梁检测算法.该方法首先根据图像的内容自动分割出水域和陆地两类不同的场景,沿着水陆交界区域搜索疑似桥梁目标,有效地缩小了搜索范围;然后提取图像的素描特征,抑制相干斑噪声的干扰;最后根据素描特征的几何特性定义桥梁的隶属度函数,实现桥梁目标的检测.在真实合成孔径雷达图像上的仿真实验表明,该算法有效地降低了桥梁的漏检率和误检率,具有较好的鲁棒性.Much speckle noise causes the bridge to be missing or undetected in SAR images.Aiming at the problem,we propose a novel algorithm based on scene semantic water bridge recognition.First,the image is automatically segmented into land and water scenes which narrow the search region of the bridge to the junction area.Second,the Primal Sketch features of the image are extracted to suppress the interference of speckle noise.Last,the membership function of the bridge is defined by its geometric characteristics based on the Prime Sketch features.Experiments show that the proposed algorithm effectively reduces the missing rate and error detection rate of the bridge,and has better robustness.

关 键 词：图像处理 目标检测 桥梁检测 合成孔径雷达图像 场景语义 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]