Weighted Curve Fitting Filtering Method Based on Full-Waveform LiDAR Data

LI Pengcheng; XU Qing; XING Shuai; LIU Zhiqing; ZHANG Junjun

doi:10.13203/j.whugis20150377

Volume 43 Issue 3

Mar. 2018

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Geomatics and Information Science of Wuhan University > 2018 > 43(3): 420-427. > DOI: 10.13203/j.whugis20150377

LI Pengcheng, XU Qing, XING Shuai, LIU Zhiqing, ZHANG Junjun. Weighted Curve Fitting Filtering Method Based on Full-Waveform LiDAR Data[J]. Geomatics and Information Science of Wuhan University, 2018, 43(3): 420-427. DOI: 10.13203/j.whugis20150377

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Weighted Curve Fitting Filtering Method Based on Full-Waveform LiDAR Data

1.
State Key Laboratory of Geo-information Engineering, Xi'an 710054, China
2.
Institute of Geospatial Information, Information Engineering University, Zhengzhou 450001, China
3.
Zhengzhou Campus, Army Academy of Artillery and Air Defense, Zhengzhou 450052, China

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The Open Research Fund of State Key Laboratory of Geo-information Engineering SKLGIE2016-M-3-1

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Author Bio:
LI Pengcheng, PhD, lecturer, specializes in digital photogrammetry, airborne LiDAR data processing. E-mail: lpclqq@163.com
Received Date: January 06, 2016
Published Date: March 04, 2018

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Abstract

Abstract

The important application of full-waveform LiDAR technology is to obtain high-precision DEM by making use of waveform data. The weighted curve fitting filtering method is proposed fusing waveform information. Discrete point cloud and waveform parameters are resolved by using global convergent LM. The waveform information and robust estimation theory are introduced to detect abnormal seed points. Then, the terrain curve is fitted according to waveform parameters. And the self-adaptive height difference threshold is determined in consideration of the window size and mean square error. The waveform data in urban, farmland and mountain areas from "WATER (watershed allied telemetry experimental research)" are selected for experiments. Experimental results prove that compared with traditional method, waveform decomposition results from proposed method are more reliable, the accuracy of point cloud filtering is further improved and the proposed method has highly practical value.
- full-waveform LiDAR,
- waveform decomposition,
- point cloud filtering,
- global convergent LM,
- ground seed points,
- weighted curve fitting

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Weighted Curve Fitting Filtering Method Based on Full-Waveform LiDAR Data

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