摘要
用地形三维激光扫描仪监测陡坡表面的细微变化,关键技术之一是对原始点云的精确滤波,即从密集点云中准确滤除非地形点,保留真实地形点。针对地势陡峭、表面复杂、植被多、密度分布极不均匀的陡坡点云,笔者发展了一种双重滤波方法:在对原始点云进行投影面变换的基础上,采用变窗口均值限差法滤除明显的非地形点,完成粗滤波;通过局部区域增长法找出绝大多数地形点,以占优势的地形点为参考,用局部最小二乘曲面拟合法对剩余未分类数据点进行检核,分离出非地形点,完成精滤波。文中选用3个不同类型的陡坡点云实例验证了该方法对于陡坡密集点云具有良好的滤波效果。该算法对野外大场景三维激光扫描点云滤波也有一定的参考价值。
Point cloud filtering is a difficult problem for deformation monitoring with 3D terrestrial scanner,especially for some steep slope that has complex surface,wide coverage vegetation,and inhomogeneous density point cloud.In this paper,the author developed an effective double-filtering algorithm to solve the above problem.The algorithm has four steps：First,to transform the coordinates of the point cloud through a projection on a plane,which is fitted though least square algorithm with original point clouds,this operation slows down the steep slope;Secondly,to remove away obvious non-topographic points using a variable size mean tolerance value algorithm;Thirdly,to find out most of real topographic points using an algorithm called local regional growing;Fourthly,Fitting least square curves with local real topographic points,using these curves to check unclassified points,separate real topographic points from non-topographic points.The former two steps called rough-filtering and the latter two steps called precise-filtering.The author selected three types of sleep slope point cloud data to verify the algorithm,result proves that the algorithm has good effect and can meet the requirement.The algorithm also has referential value for other outdoor point clouds.
出处
《地理与地理信息科学》
CSSCI
CSCD
北大核心
2011年第1期7-10,F0002,共5页
Geography and Geo-Information Science
关键词
点云
投影变换
局部区域增长
最小二乘曲面拟合
双重滤波
point cloud
project conversion
local regional growing
least square curve fitting
double-filtering
