测绘通报 ›› 2021, Vol. 0 ›› Issue (8): 7-13,36.doi: 10.13474/j.cnki.11-2246.2021.0232

• 学术研究 • 上一篇    下一篇

机载LiDAR建筑物点云渐进提取算法

高智梅1, 王竞雪1,2, 沈昭宇1   

  1. 1. 辽宁工程技术大学测绘与地理科学学院, 辽宁 阜新 123000;
    2. 西南交通大学地球科学与环境工程学院, 四川 成都 611756
  • 收稿日期:2020-08-13 出版日期:2021-08-25 发布日期:2021-08-30
  • 通讯作者: 王竞雪。E-mail:xiaoxue1861@163.com
  • 作者简介:高智梅(1994-),女,硕士生,主要研究方向为机载雷达点云分类与三维建模。E-mail:1120053709@qq.com
  • 基金资助:
    国家自然科学基金(41871379)

Aerial LiDAR building point-cloud progressive extraction algorithm

GAO Zhimei1, WANG Jingxue1,2, SHEN Zhaoyu1   

  1. 1. School of Geomatics, Liaoning Technical University, Fuxin 123000, China;
    2. Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
  • Received:2020-08-13 Online:2021-08-25 Published:2021-08-30

摘要: 针对机载LiDAR建筑物点云提取过程中易受植被的影响的问题,本文提出了一种机载LiDAR建筑物点云的渐进提取算法。首先通过布料模拟滤波算法对地面点云与非地面点云进行区分,在此基础上利用最大类间方差法算法(Otsu)对非地面点云进行阈值分割,提取初始建筑物点云;然后根据点云的连通性对初始建筑物点云进行密度聚类分割(DBSCAN),剔除离群噪声点;最后通过Alpha Shape算法实现建筑物点云的边缘提取。本文选取ISPRS官网提供的3组典型城区LiDAR点云数据进行试验,试验结果表明,本文算法可达到较好的建筑物点云提取效果。

关键词: 机载LiDAR, 建筑物点云提取, 最大类间方差法, 密度聚类, Alpha Shape

Abstract: Aiming at the problem that is easily affected by adjacent vegetation, a building point-cloud progressive extraction algorithm is proposed in this paper for airborne LiDAR. Firstly, the ground point-clouds and the non-ground point-clouds are distinguished by using the cloth simulation filter. Next, the initial building point-clouds are extracted by using Otsu to get threshold to segment the non-ground point-clouds on the basis. Then, DBSCAN is used to eliminate outlier noise points on the initial building point-clouds through the connectivity of the point-cloud. Finally, the edge of the building is obtained through the Alpha Shape algorithm. The experimental selectes three sets of LiDAR point-cloud dates of different type of urban building provided by the ISPRS official website. The result shows that the algorithm of this paper can achieve the extraction of airborne LiDAR building point-cloud better.

Key words: aerial LiDAR, building point-cloud extraction, Otsu, DBSCAN, Alpha Shape

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