Road Extraction from High Resolution Remote Sensing Image based on Shape Analysis with Gestalt Theory |
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Authors: | Cong Ming Duan Chenxi Xu Miaozhong Tao Yiting |
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Affiliation: | (1.College of Geology Engineering and Geomatics,Chang’an University,Xi’an 710054,China;;2.State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China); |
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Abstract: | Simulating the psychological experience of human vision,a road extraction model based on the format tower is proposed to extract the road in the high resolution remote sensing image from the perspective of morphology.Firstly,based on the spectral and texture information,the suspected road targets are extracted by using segmentation technology.Then these targets are classified according to their reliability and extract the road targets for each category.Finally,three types of identified road information are verified and merged,and the continuous smooth road extraction results are obtained.Experiments on real high resolution images show that the results are consistent with the visual perception of the human eye,and the overall classification accuracy is higher,indicating that the algorithm is effective and feasible and has good use value. |
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Keywords: | Road extraction Gestalt theory Image thinning Shape recognition High resolution remote sensing image |
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