基于机载LiDAR点云数据的建筑物提取方法研究

Research on Building Extraction Method Based on Airborne LiDAR Point Cloud Data

为了从机载LiDAR点云数据中快速、高效提取得到建筑物点,为建筑物三维模型重建、智慧城市建设提供数据支撑,本文提出了一种机载LiDAR点云数据的建筑物提取方法。具体实现步骤为:首先,对原始机载Li-DAR点云数据进行去噪、地面点滤波等预处理;其次,根据构建不规则三角网确定种子点进行区域生长得到初始建筑物点云;最后,对初始建筑物点云进行主成分分析等处理得到精细化建筑物点云。使用实测机载LiDAR点云数据进行实验,并对比不同方法提取建筑物点云结果。结果表明:本文方法较另外两种方法提取建筑物点云效果更好,精度更高,对于不同地形具有良好的适应性。

In order to quickly and efficiently extract building points from Airborne LiDAR point cloud data and provide data support for building 3D model reconstruction and smart city construction,this paper proposes a building extraction method from airborne LiDAR point cloud data.The specific implementation steps are as follows:first,preprocessing the original airborne LiDAR point cloud data such as denoising and ground point filtering;secondly,according to the seed points determined by constructing triangulated irregular network,the initial building point cloud is obtained by region growing;Finally,the initial building point cloud is processed by principal component analysis to obtain the refined building point cloud.Experiments are carried out using the measured airborne LiDAR point cloud data,and the results of different methods for extracting building point cloud are compared.The results show that this method has better effect and higher accuracy than the other two methods and has good adaptability to different terrains.