Auto-extraction of road intersection from high resolution remote sensing image
CAI Hongyue1,2, YAO Guoqing3
1. ChinaRS Geoinformatics Co., Ltd, Tianjin 300384, China;
2. Tianjin High Resolution Remote Sensing Information Technology Enterprise Key Lab, Tianjin 300384, China;
3. College of Information Engineering, China University of Geosciences(Beijing), Beijing 100083, China
Road intersection is one of the most important parts of road network, and extraction of road intersection information plays a significant role in such aspects as road network extraction, image registration and vehicle navigation. However, the research on extracting road intersections from remote imagery is insufficient. In view of the characteristics of road intersections in high resolution remote sensing imagery, the authors propose an approach to auto-extraction of road intersection in this paper. On the basis of image preprocessing, detection of homogeneous circular area by multi-scale structure elements was firstly used to extract alternative road intersections, which included gradient transformation and morphological transformation. Secondly, feature extraction for alternative road intersections was processed in order to further refine the result and get the central position for each choice. Finally, angular texture signature was extracted for each central position and road intersections were identified by valley finding. The experimental results show that the method presented in this paper can extract urban road intersections efficiently and has fairly good accuracy for complex urban context.
蔡红玥, 姚国清. 高分辨率遥感图像道路交叉口自动提取[J]. 国土资源遥感, 2016, 28(1): 63-71.
CAI Hongyue, YAO Guoqing. Auto-extraction of road intersection from high resolution remote sensing image. REMOTE SENSING FOR LAND & RESOURCES, 2016, 28(1): 63-71.
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2016, Vol. 28 
