Aerial Lidar Point Cloud Voxelization with its 3D Ground Filtering Application

Abstract

Compared to raster grid, Triangulated Irregular Network (TIN), and point cloud, the benefit of voxel representation lies in that the implicit notion of adjacency and the true 3D representation can be presented simultaneously. A binary voxel-based data (BVD) model is proposed to reconstruct aerial lidar point cloud and based on the constructed model 3D ground filtering (V3GF) is developed for separating ground points from unground ones. The proposed V3GF algorithm selects the lowest voxels with a value of 1 as ground seeds and then labels them and their 3D connected set as ground voxels. The ISPRS benchmark dataset are used to compare the performance of V3GF with those of eight other publicized filtering methods. Results indicate that the V3GF improves on Axelsson's performance on five samples in terms of total error. The average Kappa coefficients for sites with relatively flat urban areas, rough slope and discontinuous surfaces are 92.49 percent, 72.23 percent and 61.27 percent, respectively.