In this paper, a framework for adjusting mobile laser scanning point cloud data to improve the accuracy is proposed by integrating high resolution UAV images and MLS. First, aerial triangulated images with a few high accuracy ground control points are taken as control information. Then, a hierarchical strategy is proposed for robust pairwise registration of feature points between point cloud and images, so as to find the deviation of the point cloud. In the next step, a shape-preserving piecewise cubic interpolating method is employed to fit the time dependent error model of the trajectory. Finally, experiments are given to prove the effectiveness of proposed framework.
Gao, Y., Huang, X., Zhang, F., Fu, Z., & Yang, C. (2015). Automatic geo-referencing mobile laser scanning data to UAV images. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives (Vol. 40, pp. 41–46). International Society for Photogrammetry and Remote Sensing. https://doi.org/10.5194/isprsarchives-XL-1-W4-41-2015