Fine Registration of Mobile and Airborne LiDAR Data Based on Common Ground Points

Abstract

Light Detection and Ranging (LiDAR), as an active remote sensing technology, can be mounted on satellite, aircraft, vehicle, tripod and other platforms to acquire three-dimensional information of the earth surface efficiently. However, it is difficult to obtain omnidirectional three-dimensional information of the earth surface using a LiDAR system from a single platform. So the integration of multi-platform LiDAR data, in which data registration is a core part, has become an important topic in geospatial information processing. In this paper, the iterative closest common ground points registration method is proposed. Firstly, the possible common ground points of mobile and airborne LiDAR data are extracted. And then the adaptive octree structure is utilized to thin the LiDAR ground points, which make mobile and airborne LiDAR ground points have the same point density. Finally, the fine registration parameters are calculated by the iterative closest point (ICP) method, in which the thinned ground points from two sources are input data. The innovation of this method is that the common ground points and adaptive octree structure are used to optimize the input data of iterative closest point, which overcomes the registration difficulty caused by different perspectives and resolutions of mobile and airborne LiDAR. The proposed method was tested in this paper and can effectively realize the fine registration of mobile and airborne LiDAR data and make the facade points acquired by mobile LiDAR and the roof points acquired by airborne LiDAR fitter.