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

fYear

2013

fDate

16-18 Jan. 2013

Firstpage

104

Lastpage

107

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ISDEA.2012.32

Filename

6454773