一种改进的激光点云数据精简算法
Improved reduction algorithm for laser point cloud data
樊彦国 1杨洪旭 1任启飞1
作者信息
- 1. 中国石油大学 华东，山东 青岛 266580
- 折叠
摘要
随着三维激光扫描仪获取的点云数据量越来越大，激光点云数据精简已成为测绘领域中的一个新的研究热点。在对点云数据分层技术研究的基础上，将二维平面曲线精简算法—Douglas-Peucker 算法拓展到三维空间并进行改进，使得算法在处理前不需要已知点云间的邻接关系，可以对三维散乱点云数据进行直接处理。借助于 Matlab 平台编程实现点云数据精简，并利用程序构建精简后的点云数据的网格模型。通过与原始点云的网格模型进行对比分析，实验表明此改进算法的精简效果比较理想。
Abstract
With the increase of point cloud data gained by three dimensional laser scanner,the reduction of laser point cloud data has been a research hotspot in the field of Geomatics Engineering in recent years.Based on layer technology research of point cloud data,an improved algorithm by expanding two-dimensional plane curve algorithm -Douglas-Peucker algorithm into three-dimensional space is proposed,which do not need to get the adjacency relation of known point cloud data before dealing with the data,thus it can deal with three-dimensional scattered point cloud data direct-ly.A grid model by means of the Matlab platform was built to realize the reduction of the point cloud data.Compared with the grid model of the original ones,the effect of the new algorithm is better.
关键词
点云/数据精简/点云分层/Douglas/-Peucker/Matlab/软件Key words
point cloud/data reduction/point cloud layer/Douglas-Peucker/Matlab引用本文复制引用
出版年
2016
NETL
NSTL
维普
万方数据