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Remote Sens. 2017, 9(9), 958; doi:10.3390/rs9090958

A Multi-Constraint Combined Method for Ground Surface Point Filtering from Mobile LiDAR Point Clouds

School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
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Received: 12 August 2017 / Revised: 3 September 2017 / Accepted: 13 September 2017 / Published: 15 September 2017
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Abstract

Point cloud filtering is an essential preprocessing step in 3D (three-dimensional) LiDAR (light detection and ranging) point cloud processing. The filtering of mobile LiDAR scanning point clouds is much more challenging due to their non-uniform distribution, the large-scale of missing data areas and the existence of both large size objects and small land features. This paper proposes a new filtering method that combines range constraint, slope constraint and angular position constraint to filter ground surface points from mobile LiDAR point clouds. Firstly, a cylindrical coordinate system (CCS) is established for each block of mobile LiDAR point clouds and three attributes of mobile LiDAR points, i.e., the angular position attribute (AA), longitudinal distance attribute (LA) and range attribute (RA), are computed. Then, the mobile LiDAR point clouds are structured into a grid according to the AA and LA. Finally, the point clouds are filtered by a single cross-section filter (SCSF) using range constraint and slope constraint, followed by a multiple cross-section filter (MCSF) using range constraint and angular position constraint. Five datasets are used to validate the proposed method. The experimental results show that the proposed new filtering method achieves an average type I error, type II error, and total error of 1.426%, 1.885%, and 1.622%, respectively. View Full-Text
Keywords: mobile LiDAR scanning; point clouds; ground surface points; filtering; classification mobile LiDAR scanning; point clouds; ground surface points; filtering; classification
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Yan, L.; Liu, H.; Tan, J.; Li, Z.; Chen, C. A Multi-Constraint Combined Method for Ground Surface Point Filtering from Mobile LiDAR Point Clouds. Remote Sens. 2017, 9, 958.

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