基于微分形态学断面的机载LiDAR数据滤波新方法

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。

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

This paper proposes a new filtering method for LiDAR Data. The proposed approach constructs the connectivity of a grid over the LiDAR point-cloud in order to perform multi-scale data decomposition. 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 Photogrammetry and Remote Sensing (ISPRS) reference dataset is used to test the method. The experimental results show that the proposed method can effectively remove non-ground points, keep the ground points, and is effective at minimizing total error rates.