NDLI: A Filtering Algorithm of Airborne LiDAR Points Cloud Based on Least Square

Content Provider	IEEE Xplore Digital Library
Author	Cheng Yinglei Zhao Huizhen Qu Yayun Qiu Langbo
Copyright Year	2014
Description	Author affiliation: Inf. & Navig. Inst., Air Force Eng. Univ., Xi'an, China (Cheng Yinglei; Zhao Huizhen; Qu Yayun; Qiu Langbo)
Abstract	Filtering algorithm based on least square method can get digital elevation model of high precision, but the filtering effect is poor if non-ground point set is big. In order to solve this problem, points of smaller elevation are used to initial curved surface fitting, which has smaller calculation compared with fitting by all points. The curved surface is closer to the ground, making it conducive to the subsequent iteration. Only ground point set is processed in the subsequent iteration, so the processing is simple. The experimental results show that the algorithm has smaller error and can filter out large part of non-ground points effectively.
Starting Page	24
Ending Page	27
File Size	279761
Page Count	4
File Format	PDF
e-ISBN	9781479942619
DOI	10.1109/ISDEA.2014.14
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-06-15
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Laser radar Three-dimensional displays Filtering Fitting Filtering algorithms Lidar Surface fitting Least Square Points Cloud
Content Type	Text
Resource Type	Article

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A Filtering Algorithm of Airborne LiDAR Points Cloud Based on Least Square