An improved voxel filtering method based on octree structure and point density
Shaoyang Huang · 2023
In response to the issues of information loss in high-density regions and alteration of the original point cloud shape caused by voxel-based point cloud filtering, a voxel filtering method based on octree and point density is proposed. After voxelization using the octree, within each voxel, all points are arranged in ascending order based on their distances from the voxel center point. Starting from the nearest point to the voxel center point and at a preset interval, points are selected, and these selected points constitute the new point cloud, representing the filtered point cloud. Experimental results indicate that the proposed method not only better preserves the original point cloud's shape but also retains information about high-density areas. Compared to voxel filtering, the proposed method exhibits smaller point-to-point distance errors between the filtered point cloud and the original point cloud. This approach introduces a novel perspective for point cloud simplification.