Hierarchical Registration Method for Airborne and Vehicle LiDAR Point Cloud
AbstractA new hierarchical method for the automatic registration of airborne and vehicle light detection and ranging (LiDAR) data is proposed, using three-dimensional (3D) road networks and 3D building contours. Firstly, 3D road networks are extracted from airborne LiDAR data and then registered with vehicle trajectory lines. During the registration of airborne road networks and vehicle trajectory lines, a network matching rate is introduced for the determination of reliable transformation matrix. Then, the RIMM (reversed iterative mathematic morphological) method and a height value accumulation method are employed to extract 3D building contours from airborne and vehicle LiDAR data, respectively. The Rodriguez matrix and collinearity equation are used for the determination of conjugate building contours. Based on this, a rule is defined to determine reliable conjugate contours, which are finally used for the fine registration of airborne and vehicle LiDAR data. The experiments show that the coarse registration method with 3D road networks can contribute to a reliable initial registration result, and the fine registration using 3D building contours obtains a final registration result with high reliability and geometric accuracy. View Full-Text
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Cheng, L.; Wu, Y.; Tong, L.; Chen, Y.; Li, M. Hierarchical Registration Method for Airborne and Vehicle LiDAR Point Cloud. Remote Sens. 2015, 7, 13921-13944.
Cheng L, Wu Y, Tong L, Chen Y, Li M. Hierarchical Registration Method for Airborne and Vehicle LiDAR Point Cloud. Remote Sensing. 2015; 7(10):13921-13944.Chicago/Turabian Style
Cheng, Liang; Wu, Yang; Tong, Lihua; Chen, Yanming; Li, Manchun. 2015. "Hierarchical Registration Method for Airborne and Vehicle LiDAR Point Cloud." Remote Sens. 7, no. 10: 13921-13944.