Abstract: Objective The mosaicking of point clouds is a key step in point cloud processing.We propose a pointcloud mosaicking technology for multi-station laser scanning based on 2Dimage matching and 3Dcor-responding feature point refinement to solve the problems in existing point cloud mosaicking method-ologies for multi-station laser scanning,such as low efficiency,poor accuracy,and low automation.Firstly,the 2Dimages are generated from the derivative information from laser scanning data using in-terpolation algorithms.Secondly,2Dcorresponding feature points are obtained using GPU accelera-tion SIFT image matching,eliminating gross errors.Finally,3Dcorresponding feature points are ac-quired using an inversion algorithm;identifying whether they are same corresponding feature points inthe 3Dpoint cloud.Experiments demonstrate the feasibility and effectiveness of the proposed method.