基于LiDAR点云的高压电塔自动提取算法  

Automatic Extraction Algorithm of High Voltage Pylon Based on LiDAR Point Cloud

作　　者：单丽杰 岳建平[1] Shan Lijie;Yue Jianping(School of Earth Science and Engineering.Hohai Uniuersity,Nanjing,Jiangau 211100,China)

机构地区：[1]河海大学地球科学与工程学院,江苏南京211100

出　　处：《激光与光电子学进展》2021年第24期483-489,共7页Laser & Optoelectronics Progress

基　　金：国家重点研发计划(2018YFC1508603)。

摘　　要：为提取机载LiDAR点云中的高压电塔,提出一种电塔自动提取算法。首先,对点云进行预处理,利用布料滤波算法得到地面点和非地面点;对非地面点点云进行空间规则化网格处理,根据高压电塔的高程特征进行粗提取,得到存在电塔的感兴趣区域(ROI)网格;最后,利用改进的基于密度的噪声空间聚类算法剔除ROI网格中的噪声点,进行电塔点云的精细提取。实验结果表明,本文算法可以实现LiDAR点云中高压电塔的自动提取,具有较高的自动化程度和处理效率。To extract high voltage pylons from airborne LiDAR point clouds, a pylon automatic extraction algorithm is proposed. First, the point cloud is preprocessed, and the cloth simulation filtering(CSF) algorithm is used to obtain ground points and non-ground points. Then, spatially regularized grid processing is carried out for non-ground point clouds, rough extraction is performed according to the elevation characteristics of high voltage pylons, and region of interest grids with pylons are obtained. Finally, the improved DBSCAN(density-based spatial clustering of applications with noise) algorithm is used to remove the noise points in ROI grids, and the pylon point cloud is finely extracted. The test results show that the algorithm in this paper can realize the automatic extraction of high voltage pylons from LiDAR point clouds, with a high degree of automation and a high processing efficiency.

关 键 词：遥感 激光点云 高压电塔 自动提取 规则网格 基于密度的噪声空间聚类 

分 类 号：P23[天文地球—摄影测量与遥感]