基于组合滤波算法的机载LiDAR数据DEM构建

DEM Construction for Airborne LiDAR Data Based on Combined Filtering Algorithm

针对采用单一渐进式形态学滤波处理机载激光雷达(LiDAR)数据时难以生成高质量数字高程模型(DEM)的问题,提出一种基于空间向量投影的后处理滤波方法,以剔除对DEM构建精度影响较大的近地面点。该方法以每个激光点为起点,以与距离它最近的9个网格最低点为终点构建向量,然后累加9个向量在Z方向上的投影,并将结果与预先设置的阈值比较,进而识别、分类当前激光点。为了验证所提方法的有效性,选取6组国际摄影测量与遥感协会(ISPRS)提供的不同地形条件下的测试数据进行实验,分别将加入后处理滤波前后提取的地面点云生成1 m×1 m分辨率的DEM,并与同一研究区域的参考DEM进行线性拟合。结果表明:与单一渐进式形态学滤波算法相比,渐进式形态学滤波和基于空间向量投影的后处理滤波的组合算法在城市地区和地形连续的乡村地区可以获得更好的点云滤波精度和DEM构建精度,具有良好的适用性和可靠性。

Herein, a method of post-processing filtering based on space vector projection is proposed to eliminate the near-ground points that have a considerable impact on the accuracy of digital elevation model(DEM) construction to address the problem of difficulty in generating a high-quality DEM via single progressive morphological filtering for airborne light detection and airborne ranging(LiDAR) data. Initially, the proposed method takes each laser point as starting point and then constructs vectors with the lowest laser point of each of the nine grids closest to it at the end. Thereafter the method accumulates the projection of each of the nine vectors in the Z direction, compares the results to the preset threshold, and identifies as well as classifies the laser point. To validate the effectiveness of the proposed method, this study selects six groups of test data from the international society for photogrammetry and remote sensing(ISPRS) under different terrain conditions and generates 1 m × 1 m resolution DEM using ground points extracted before and after the post-processing filtering as well as performs linear fitting with reference DEM in the same research area. The results show that when compared with a single progressive morphological filtering algorithm, the combined algorithm of progressive morphological filtering and post-processing filtering based on space vector projection can achieve higher precision of point cloud filtering and DEM construction in urban area and rural area with continuous terrain as well as has good applicability and reliability.