An entropy-based filtering approach for airborne laser scanning data |
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| Affiliation: | 1. School of Geosciences, China University of Petroleum, Qingdao 266555, China;2. Faculty of Geomatics, East China Institute of Technology, Nanchang 330013, China;3. Xiamen University, Xiamen 361005, China;1. Department of Optical Engineering, Utsunomiya University, Utsunomiya, Japan;2. Center for Optical Research and Education (CORE), Utsunomiya University, Utsunomiya, Japan;1. Istituto per l’Ambiente Marino Costiero, IAMC-CNR sede, Calata Porta di Massa-Porto di Napoli, 80133 Napoli, Italy;2. Centre for Marine Science and Technology, Curtin University, GPO Box U1987, Perth, WA 6845, Australia;1. Smt. Chandaben Mohanbhai Patel Institute of Computer Applications, CHARUSAT Campus, Changa, Anand 388421, Gujarat, India;2. Department of Computer Science & Engineering, Thapar Institute of Engineering and Technology, Patiala 147004, Punjab, India;1. Nanjing University of Aeronautics and Astronautics, School of Electronic and Information Engineering, Yudao Street No. 29, Nanjing, 210016, China;2. The Yellow River Sediment Key Laboratory of Ministry of Water Resources, Shunhe Street No. 45, Zhenzhou, 450003, China;3. The Key Laboratory of Rivers and Lakes Governance and Flood Protection of Yangtse River Water Conservancy Committee, Huangpu Street No. 23, Wuhan, 430010, China;4. State Key Laboratory of Urban Water Resource and Environment, Nangang District, Huanghe Street No. 73, Harbin, 150090, China |
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| Abstract: | Parameter-tuning is a challenging task when generating digital terrain models from airborne laser scanning (light detection and ranging, LiDAR) data. To address this issue, this paper presents a filtering method for near-infrared laser scanning data that exploits the principle of entropy maximization as the optimization objective. The proposed approach generates ground elevation of point cloud by constructing a triangulated irregular network, calculates the entropy of the elevation from different parts, and automatically separates ground and non-ground points by the principle of entropy maximization. Experimental results from different ground surfaces show that the proposed entropy-based filtering method can effectively extract bare-earth points from the point cloud without adjusting thresholds. |
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| Keywords: | DEM LiDAR point clouds Filtering Entropy optimization |
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