Car Detection by Using High Resolution Remote Sensing Image Based on Background Iterative Search
WU Xiao-Bo1,2, YANG Liao1, SHEN Jin-Xiang1,2, WANG Jie1,2
1. Remote Sensing and GIS Application Laboratory, Xinjiang Ecology and Geography Institute, Chinese Academy of Sciences, Urumqi 830011, China;
2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China
In the traditional Space-to-Earth car detection system,thermal infrared,radar or aerial image data are often used, while high-resolution satellite remote sensing data have rarely been employed. To solve this problem, this paper proposes a new method for car detection based on high resolution satellite images,which is named BIS (Background Iterative Search). Firstly, according to the local differences between the object and the background,the background is searched and removed,and the preliminary car detection is achieved based on the material properties of cars. Secondly,the dynamic twin peak threshold method is used to separate roads from non-roads,and roads are roughly extracted based on shape features. Lastly,the correct car objects are obtained by constraining the elementary ones with the derived road information. The BIS method was applied with IKONOS and QuikBird data and proved to be effective.
吴小波, 杨辽, 沈金祥, 王杰. 基于背景迭代搜索的高分辨遥感图像汽车检测[J]. 国土资源遥感, 2011, 23(4): 46-51.
WU Xiao-Bo, YANG Liao, SHEN Jin-Xiang, WANG Jie. Car Detection by Using High Resolution Remote Sensing Image Based on Background Iterative Search. REMOTE SENSING FOR LAND & RESOURCES, 2011, 23(4): 46-51.
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2011, Vol. 23 
