Laser & Optoelectronics Progress, Volume. 55, Issue 1, 12803(2018)
Digital Surface Model Accuracy Improvement Based on Edge Line Automatic Extraction of Building Laser Point Cloud
During the scanning process of airborne laser radar (LiDAR), ground edge line in the back of the building is always shaded, edge point data of building surface are usually hard to be obtained accurately, so a digital surface model (DSM) with low precision is obtained by three dimensional reconstruction with these low accurate LiDAR point cloud data. In order to improve the DSM accuracy, we propose an edge line automatic extraction algorithm. This approach initially extracts local point cloud of building surface edge to fit local trend surface. Then two neighborhood trend surfaces are used to compute the intersection''s equation and add edge point cloud data. Finally, using the laser point cloud of the building with the additional extracted edge points, we rebuilt the DSM of the building, and the accuracy of the reconstructed DSM with adding the edge points is compared with that of the DSM without adding the edge points. Simulated results show that the accuracy of the DSM reconstructed by this method can be improved significantly.
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Miao Song, Wang Jianjun, Li Yunlong, Fan Yuanyuan. Digital Surface Model Accuracy Improvement Based on Edge Line Automatic Extraction of Building Laser Point Cloud[J]. Laser & Optoelectronics Progress, 2018, 55(1): 12803
Category: Remote Sensing and Sensors
Received: Jun. 11, 2017
Accepted: --
Published Online: Sep. 10, 2018
The Author Email: Jianjun Wang (wangjianjun@sdut.edu.cn)