一种基于偏度平衡的LiDAR点云滤波算法

Filtering Method for LiDAR Point Clouds Based on Skewness Balancing

在回顾现有机载LiDAR点云数据滤波算法的基础上,引入统计学偏度与峰度的概念,提出了一种新的基于偏度平衡的点云滤波算法,并重点对算法性能展开深入分析。通过对比实验得出结论:与传统滤波方法相比,该算法完全自动化的特点以及高效的运算效率具有较大的实际应用价值。

By reviewing the existing filtering algorithms, the concepts of skewness and kurtosis in statistics are introduced to propose a novel point cloud filtering method based on skewness balancing, and the emphasis is placed on intensive performance analysis of the algorithm. Comparison experiments show compared with the traditional filtering methods, the proposed method has great practical application value due to its complete automation and high efficiency characteristics.