隧道激光扫描点云数据下采样滤波处理对计算结果的影响研究

Research on the Influence of Downsampling Filtering on the Calculation Results of Tunnel Laser Scanning Point Cloud Data

随着科技的不断进步,采用三维激光扫描技术能为隧道工程的建设与运营提供精准的指导,从而产生巨大的效益,然而运用该技术获取的隧道点云数据量巨大,严重制约了后续点云数据处理的效率。为了促进该技术的广泛应用,文章研究了一种基于体素栅格化网格下采样的点云数据滤波算法,该方法的原理是利用三维体素栅格将点云数据集划分为不计其数的小立方体,然后通过计算保留下三维体素栅格中满足要求的数据点,即可在维持点云数据原有几何特征的基础上去除重复点,实现点云数据下采样滤波处理。最后分析了该方法对隧道点云数据量处理结果的影响,综合考虑滤波时间、简化率、精度等因素,为实际工程中下采样滤波参数的选用提供了合理建议。

With the continuous advancement of science and technology, the use of 3D laser scanning technology can provide accurate guidance for the construction and operation of tunnel projects, thereby producing huge benefits. However,the huge amount of tunnel point cloud data obtained by this technology seriously restricts the efficiency of subsequent point cloud data processing. In order to promote the wide application of this technology, this paper studies a point cloud data filtering algorithm based on voxel grid downsampling. The principle of this method is to use 3D voxel grid to divide the point cloud dataset into countless small cubes,and then retain the data points that meet the requirements in the 3D voxel grid by calculation, so as to remove the repeated points on the basis of maintaining the original geometric characteristics of the point cloud data, and realize the downsampling filtering processing of the point cloud data. Finally,the influence of this method on the processing results of tunnel point cloud data is analyzed. Factors such as filtering time, simplification rate, and accuracy are comprehensively considered, and reasonable suggestions are provided for the selection of downsampling filtering parameters in practical engineering.