机载LiDAR点云数据的二面角滤波算法

机载LiDAR是获取地表DEM的重要技术之一。本文针对机载LiDAR点云数据在复杂城区环境下的大型建筑及低矮地物滤波问题,提出一种新的二面角滤波法。利用空间二面角的平面角可以表达空间两相交平面相对位置的原理,实现机载LiDAR点云数据滤波。首先,算法提取点云数据中的高程突变点,以非突变点的二面角余弦均值稳定性作为判定迭代结束的条件;其次,分别统计高程突变和非突变点集的二面角余弦值频率分布,以交点处对应余弦值和最后一次迭代的坡度值作为LiDAR点云滤波的判定条件;最后,利用数学形态学“开”算子,去除残留低矮植被,得到可靠的滤波结果。对同一区域机载LiDAR点云数据,通过“二面角法”与“渐进三角网法”进行滤波处理。实验结果表明,二面角滤波法能有效地降低地物点错分为地面点的百分率,且在去除地物信息的同时能良好地保留地形特征。

Dihedral Angle Filtering Algorithm for Airborne LiDAR Point Cloud Data

Airborne LiDAR is one kind of the technologies for obtaining ground surface DEM. On the analysis of the airborne LiDAR point cloud filtering algorithms, this paper proposes a new filtering algorithm-dihedral filtering. The algorithm is based on the theory that can express the relative position of two intersect planes in space, to achieve the airborne LiDAR point cloud data filtering process. Firstly, the elevation-mutate points are extracted from point cloud data. The iteration ends when the stability of the cosine of non-mutated points′ dihedral angle reaches required level. Then, the frequency distributions of the cosine of both mutated and non-mutated points′ dihedral angle are counted, and draws a line chart. Ground points and non-ground points are classified based on the intersection′s cosine of line chart and slope value of the last iteration. Finally, the open operator of the mathematical morphology is used to remove low vegetation, and the reliable results are obtained. Comparing with ′Progressive TIN Method′, the misjudged percentage of the non-ground points were effectively reduced. Dihedral method can retain topographical information while filtering terrestrial object information.