Automatic and Accurate Mosaicking of Point Clouds from Multi-station Laser Scanning

The mosaicking of point clouds is a key step in point cloud processing.We propose a point cloud mosaicking technology for multi-station laser scanning based on 2D image matching and 3D corresponding feature point refinement to solve the problems in existing point cloud mosaicking methodologies for multi-station laser scanning,such as low efficiency,poor accuracy,and low automation.Firstly,the 2D images are generated from the derivative information from laser scanning data using interpolation algorithms.Secondly,2D corresponding feature points are obtained using GPU acceleration SIFT image matching,eliminating gross errors.Finally,3D corresponding feature points are acquired using an inversion algorithm;identifying whether they are same corresponding feature points in the 3D point cloud.Experiments demonstrate the feasibility and effectiveness of the proposed method.