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Remote Sens. 2015, 7(8), 10996-11015;

Semi-Global Filtering of Airborne LiDAR Data for Fast Extraction of Digital Terrain Models

School of Remote Sensing and Information Engineering, 129 Luoyu Road, Wuhan University, Wuhan 430079, China
Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China
Lyles School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA
Author to whom correspondence should be addressed.
Academic Editors: Juha Hyyppä, Nicolas Baghdadi and Prasad S. Thenkabail
Received: 8 May 2015 / Revised: 24 July 2015 / Accepted: 20 August 2015 / Published: 24 August 2015
(This article belongs to the Special Issue Lidar/Laser Scanning in Urban Environments)
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Automatic extraction of ground points, called filtering, is an essential step in producing Digital Terrain Models from airborne LiDAR data. Scene complexity and computational performance are two major problems that should be addressed in filtering, especially when processing large point cloud data with diverse scenes. This paper proposes a fast and intelligent algorithm called Semi-Global Filtering (SGF). The SGF models the filtering as a labeling problem in which the labels correspond to possible height levels. A novel energy function balanced by adaptive ground saliency is employed to adapt to steep slopes, discontinuous terrains, and complex objects. Semi-global optimization is used to determine labels that minimize the energy. These labels form an optimal classification surface based on which the points are classified as either ground or non-ground. The experimental results show that the SGF algorithm is very efficient and able to produce high classification accuracy. Given that the major procedure of semi-global optimization using dynamic programming is conducted independently along eight directions, SGF can also be paralleled and sped up via Graphic Processing Unit computing, which runs at a speed of approximately 3 million points per second. View Full-Text
Keywords: LiDAR; filtering; classification; digital terrain model; semi-global optimization; GPU LiDAR; filtering; classification; digital terrain model; semi-global optimization; GPU

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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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Hu, X.; Ye, L.; Pang, S.; Shan, J. Semi-Global Filtering of Airborne LiDAR Data for Fast Extraction of Digital Terrain Models. Remote Sens. 2015, 7, 10996-11015.

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