利用GIS与贝叶斯网络进行高分辨率SAR影像道路损毁信息提取  

Road Damage Extraction from High-Resolution SAR Image Based on GIS Data and Bayes Network

作　　者：眭海刚[1] 华凤[1] 范一大 刘俊怡[1] 

机构地区：[1]武汉大学测绘遥感信息工程国家重点实验室,湖北武汉430079 [2]民政部国家减灾中心,北京100124

出　　处：《武汉大学学报（信息科学版）》2016年第5期578-583,共6页Geomatics and Information Science of Wuhan University

基　　金：国家重点基础研究发展规划(2012CB719906);国家高技术研究发展规划(2013AA122301);国家自然科学基金(41101414);高分辨率对地观测系统重大专项~~

摘　　要：合成孔径雷达(synthetic aperture radar,SAR)具有全天时、全天候观测,穿透能力强等特点,在灾害监测与评估、资源勘探等方面得到广泛应用,但其固有的相干斑噪声严重限制了单一利用SAR影像进行快速的信息获取。本文提出了一种基于GIS与贝叶斯网络的高分辨率SAR影像道路损毁信息提取方法。在GIS数据的辅助下,利用水平集分割与改进的D1检测融合的方法在影像上提取疑似道路损毁区域;再综合多证据及疑似损毁区观测值构建贝叶斯网络模型,对疑似损毁区进一步判断提取出实际道路损毁区域。实验结果表明,该方法能够快速、准确地对道路损毁信息进行提取。Synthetic aperture radar （SAR） permits all-time, all-weather observation and strong penetration, and is widely used in disaster monitoring and evaluatiort, resource exploration, and military reconnaissance. However, speckle noise seriously affects the quality of SAR images, thus limiting the use of SAR image for quick access to information. In this paper, a new road damage extraction method for high-resolution SAR images based on GIS data and Bayes network is proposed. Guided by GIS data, suspected damaged roads are extracted using the fusion of level-set segmentation and an improved D1 line detection. A Bayes network is applied to further confirm real damaged roads based on multi- evidence and the observed values from suspected damage road, to eliminate the false-alarms from the SAR images. Experimental results indicate that our proposed method can extract road damage information quickly and accurately.

关 键 词：SAR 高分辨率影像 GIS数据 损毁信息提取 

分 类 号：P237.4[天文地球—摄影测量与遥感] P208[天文地球—测绘科学与技术]