摘要
点云数据滤波处理是获取高精度数字地面模型的关键,而滤波的基本原理是基于某一邻域内高程的突变。在海量、离散的点云数据中,搜索某一邻域的速度将直接影响滤波处理的效率。应用k-d树组织点云数据,不需要先验地知道点云数据间的拓扑关系便可以快速确定其中某一点的邻域点集,从而大大地提高滤波速度。
Point cloud data filtering is one of the most important tasks in gaining the high-accuracy Digital Terrain Model（DTM）,and the basic principle of filtering is based on elevation abrupt changes in one neighbor area.To great quantity discrete point cloud data,the speed for searching one point s neighbors restricts the efficiency of data filtering.It is possible to quickly find one point s neighbors with k-d tree without prior knowing topological relations of point cloud data which improves the speed for data filtering.
出处
《测绘工程》
CSCD
2009年第5期59-62,共4页
Engineering of Surveying and Mapping
