Coregistration of LiDAR Data Based on Linear and Point Features Matching in Overlapping Strips

Today LIDAR system is the known technology for 3D data collection from earth surface which provides a fast and accurate solution for DSM generation. For LIDAR data correction، the systematic errors should be modeled that is done in system calibration. By studying the effects of different error sources on derived data، optimal flight planning can be done so that the highest accuracy for system calibration is reached. To estimate the calibration parameters، the geometric compatibility between laser footprints in the overlapped or crossed strips should be measured in a coregistration process. After data correction by applying estimated calibration parameters، the geometric compatibility of point clouds gives an estimation of the quality of final data. This paper proposes two methods for coregistration of LiDAR point clouds. In the first method، the point clouds are divided into small planar surfaces and mathematical equation of each surface is derived. Then straight lines are produced based on the intersection of the neighborhood surfaces. Finally، the linear features extracted from two strips are matched. The second method uses the SIFT algorithm to extract and match the point features. At the end، mathematical models are used in both methods to determine the shift and rotation parameters between the corresponding features. Results showed that the accuracy of the second method is about 19% higher than the first one.