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8 March 2018Automatic road extraction from high resolution remote sensing image by means of topological derivative and mathematical morphology
Automatic road extraction from High Resolution Remote Sensing Image is a challenging problem. In this paper we present a new approach for road automatically extraction which is based on topological derivative and mathematical morphology. This approach for road extraction can be divided into three main steps: using topological derivative for image segmentation, using mathematical morphology for road network identification and filtering. The experimental results show that this approach can effectively extract roads from high-resolution remote sensing image.
Hongyu Zhou,Xu Song, andGuoying Liu
"Automatic road extraction from high resolution remote sensing image by means of topological derivative and mathematical morphology", Proc. SPIE 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 1061104 (8 March 2018); https://doi.org/10.1117/12.2282998
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Hongyu Zhou, Xu Song, Guoying Liu, "Automatic road extraction from high resolution remote sensing image by means of topological derivative and mathematical morphology," Proc. SPIE 10611, MIPPR 2017: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 1061104 (8 March 2018); https://doi.org/10.1117/12.2282998