基于微分形态学断面的机载LiDAR数据滤波新方法

A New Filtering Method for Aribone LiDAR Data Based on Differential Morphological Profiles

提出一种基于微分形态学断面的机载LiDAR点云数据滤波新方法。该方法由点云数据构建规则格网,去除粗差点;对构建的每一个格网进行多尺度分解,获取初始地面点及地物点;分别利用曲面逼近及微分形态学断面构建DTM(digital terrain model),通过阈值函数判别二者之间的残差,确定最终地面点。使用国际摄影测量与遥感学会提供的测试数据进行实验,并与8种经典滤波算法比较分析,表明该方法能够有效去除地物点和保留地面点,并降低总误差。

This paper proposes a new filtering method for LiDAR Data. The proposed approach con- structs the connectivity of a grid over the LiDAR point-cloud in order to perform multi-scale data de- composition. This is realized by forming a top-hat scale-space using differential morphological profiles （DMPs） on points~ residuals from the approximated surface. The International Society for Photo- grammetry and Remote Sensing （ISPRS） reference dataset is used to test the method. The experimen- tal results show that the proposed method can effectively remove non-ground points, keep the ground points, and is effective at minimizing total error rates.