DocumentCode :
179017
Title :
A Filtering Algorithm of Airborne LiDAR Points Cloud Based on Least Square
Author :
Cheng Yinglei ; Zhao Huizhen ; Qu Yayun ; Qiu Langbo
Author_Institution :
Inf. & Navig. Inst., Air Force Eng. Univ., Xi´an, China
fYear :
2014
fDate :
15-16 June 2014
Firstpage :
24
Lastpage :
27
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.
Keywords :
curve fitting; digital elevation models; filtering theory; iterative methods; least squares approximations; optical radar; airborne LiDAR points cloud; digital elevation model; filtering algorithm; iteration; least square method; Algorithm design and analysis; Filtering; Filtering algorithms; Fitting; Laser radar; Surface fitting; Three-dimensional displays; Filtering; Least Square; Lidar; Points Cloud;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Engineering Applications (ISDEA), 2014 Fifth International Conference on
Conference_Location :
Hunan
Print_ISBN :
978-1-4799-4262-6
Type :
conf
DOI :
10.1109/ISDEA.2014.14
Filename :
6977537
Link To Document :
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