Uniform Grid Upsampling of 3D LiDAR Point Cloud Data

Airborne laser scanning light detection and ranging (LiDAR) systems are used for remote sensing topology and bathymetry. The most common data collection technique used in LiDAR systems employs a linear mode scanning. The resulting scanning data form a non-uniformly sampled 3D point cloud. To interpret and further process the 3D point cloud data, these raw data are usually converted to digital elevation models (DEMs). In order to obtain DEMs in a uniform and upsampled raster format, the elevation information from the available non-uniform 3D point cloud data are mapped onto the uniform grid points. After the mapping is done, the grid points with missing elevation information are filled by using interpolation techniques. In this paper, partial differential equations (PDE) based approach is proposed to perform the interpolation and to upsample the 3D point cloud onto a uniform grid. Due to the desirable effects of using higher order PDEs, smoothness is maintained over homogeneous regions, while sharp edge information in the scene well preserved. The proposed algorithm reduces the draping effects near the edges of distinctive objects in the scene. Such annoying draping effects are commonly associated with existing point cloud rendering algorithms. Simulation results are presented in this paper to illustrate the advantages of the proposed algorithm.