Title :
A Method for Noise Removal of LIDAR Point Clouds
Author :
Huang Zuowei ; Huang Yuanjiang ; Huang Jie
Author_Institution :
Sch. of Archit. & Urban Planning, Hunan Univ. of Technol., Zhuzhou, China
Abstract :
LiDAR can quickly and accurately obtain precision and high-density surface elevation data. In cooperation with high-precision GPS positioning technology and IMU attitude sensor, a typical noise removal algorithm of LIDAR point clouds based on FEA is proposed. Firstly point clouds is partitioned into smaller and similar units, then all of the units are classified into noise units or non-noise units with adjacency-based reasoning rules. Finally, the low noise is removed by iterative processing with finer threshold, The result shows that this method has good performance in noise removal.
Keywords :
Global Positioning System; computer graphics; finite element analysis; image denoising; inference mechanisms; iterative methods; optical radar; radar computing; radar imaging; FEA; IMU attitude sensor; LIDAR point cloud; adjacency-based reasoning rule; high-density surface elevation data; high-precision GPS positioning technology; iterative processing; noise removal algorithm; noise unit; Intelligent systems; FEA; LIDAR; noise removal; point clouds;
Conference_Titel :
Intelligent System Design and Engineering Applications (ISDEA), 2013 Third International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4673-4893-5
DOI :
10.1109/ISDEA.2012.32
