30 October 2009 An improved 1D filtering method for LIDAR point cloud
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Proceedings Volume 7494, MIPPR 2009: Multispectral Image Acquisition and Processing; 74941S (2009) https://doi.org/10.1117/12.832820
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China
Abstract
This paper discusses how to separate non-ground points from raw LIDAR point cloud. For the purpose of improving processing efficiency and precision, an improved 1-D filtering method is proposed. The entire filtering process is divided into eight steps and non-ground points are eliminated progressively. In these processing steps, a key-point detection technique is used to segment points in profile. Based on these profile segments, detailed analysis is utilized to implement segment-oriented filtering innovatively. This method makes use of entire features of segmental points for classification, so it is more accuracy and robust than traditional point-by-point classification. Two different scale datasets are used to test our method. Compared to 1-D labeling method, the proposed method is more effective and efficiency.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jing Zhang, Jing Zhang, Fang Zhang, Fang Zhang, Wanshou Jiang, Wanshou Jiang, Xiaojun Zhang, Xiaojun Zhang, Lelin Li, Lelin Li, Jianchao Wang, Jianchao Wang, Dahai Guo, Dahai Guo, } "An improved 1D filtering method for LIDAR point cloud", Proc. SPIE 7494, MIPPR 2009: Multispectral Image Acquisition and Processing, 74941S (30 October 2009); doi: 10.1117/12.832820; https://doi.org/10.1117/12.832820
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