Open AccessFiltering Processing of LIDAR Point Cloud Data
Author(s) -
Yaxiong Jin,
Xiaofang Yuan,
Zhe Wang,
Boqiang Zhai
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/783/1/012125
Subject(s) - lidar , point cloud , noise (video) , computer science , object (grammar) , remote sensing , computer vision , cloud computing , point (geometry) , data processing , artificial intelligence , geography , image (mathematics) , mathematics , geometry , operating system
During the acquisition of point cloud data by LIDAR, due to system and environment reasons, there will be a large number of discrete points and noise points in the obtained point cloud data, which will affect the extraction of target ground object information. In view of the noise introduced by the system itself and the environment where the target object is when the LIDAR is scanning, a de-noising method combining statistical filtering and bilateral filtering is proposed in this paper.