基于坡度与迭代运算的LiDAR点云数据滤波

LiDAR Point Cloud Data Filtering Based on Slope and Iterative Arithmetic

滤波是机载LiDAR数据后处理的关键步骤。总结了常见数据点的特征及滤波的基本要求,分析了基于坡度和变化窗口滤波的原理和优缺点,然后在虚拟网格、坡度滤波的基础上,优化了窗口尺寸和坡度阈值的设定,让地面种子点的筛选更加准确;同时结合迭代运算,基于现有地面点集,通过窗口内的坡度阈值判定,逐轮筛分了剩余数据点,从而得到了更精确的滤波结果。

Filtering is the key step in the airborne LiDAR data post-processing.This article summarized the characteristics of the common points and the basic requirements of filtering,analyzed the principle of the filtering based on slope and changing windows,stated its advantages and disadvantages.On the basis of virtual grid and slope filtering,optimized the window size and gradient threshold,let the point selection more accurate.At the same time,combined with the iterative algorithm,based on the existing ground point set,judged the other points through the gradient threshold by successive rounds.At last,a relatively accurate filtering result was obtained.