用于公路勘测设计的LiDAR点云抽稀算法  

LiDAR Point Cloud Thinning Algorithm for Road Survey and Design

作　　者：方程喜 隋立春[1,2] 朱海雄 

机构地区：[1]长安大学地质工程与测绘学院,陕西西安710054 [2]地理国情监测国家测绘地理信息局工程技术研究中心,陕西西安710064

出　　处：《测绘通报》2017年第10期58-61,88,共5页Bulletin of Surveying and Mapping

基　　金：国家自然科学基金(41372330)

摘　　要：传统的抽稀算法应用于公路点云数据抽稀时,往往存在不能很好地顾及地形特征,或者出现大面积点云空洞的缺陷。本文提出了一种改进的基于平均曲率算法,用于公路勘测设计中的点云数据的抽稀,该算法首先通过局部二次曲面拟合,依次求出所有点的平均曲率;然后根据平均曲率判断地形特征,并作为判别点云数据抽稀的主要准则;最后利用标记法解决了平坦路面出现大面积空洞的问题。通过试验与分析,证明了本文抽稀算法的可靠性和适用性。When the traditional thinning algorithm is applied to data extraction of road point cloud, there are many defects, such as cannot take good account of terrain features, or appear the large area point cloud hole. In this paper, an improved algorithm based on mean curvature is proposed for the extraction of point cloud data in road survey and design. Firstly, the mean curvature of all points is obtained by local quadratic surface fitting. And then according to the mean curvature to determine the terrain features, and as the main criteria for the identification of point cloud data dilution. Finally, the problem of the large area point cloud hole in the fiat road surface is solved by using the marking method. Through the experimental results and analysis, the reliability and applicability of the thinning algorithm are proved.

关 键 词：公路勘测设计 LIDAR 抽稀 平均曲率 点云空洞 

分 类 号：P237[天文地球—摄影测量与遥感]