一种基于多尺度网格的自适应LiDAR点云滤波方法

A filtering method for urban airborne LiDAR point clouds based on adaptive multi-grid size

通过实验实现一种自适应多网格尺寸城区机载激光点云滤波方法。在利用K-D树计算初始网格尺寸的基础上,通过二维网格进行点云数据管理,以网格内点高程和网格平均高程作为滤波条件,利用多网格尺寸进行滤波,从而在不需要参数条件下,实现了点云自适应滤波。选取两个城市点云数据进行实验,结果表明,该方法能取得良好的效果。

Combining the filtering advantages of grid and discrete point clouds,an adaptive multi-grid size filtering method for urban airborne LiDAR point clouds is proposed. On the basis of calculating the initial grid size by using K-D tree,the point clouds are organized using 2D grids. Points are filtered as nonground points under the condition that those points whose height is above the gird height. Multi-grid sizes are used for the filtering process so that no parameter is needed during the filtering process. Datasets of two different cities are selected for tanking the experiment,the results show that the proposed method can achieve good results without human intervention.