Registration of optical imagery and LiDAR data using an inherent geometrical constraint

作者:Zhang, WM (Zhang, Wuming)[ 1 ] ; Zhao, J (Zhao, Jing)[ 1 ] ; Chen, M (Chen, Mei)[ 1 ] ; Chen, YM (Chen, Yiming)[ 1 ] ; Yan, K (Yan, Kai)[ 1 ] ; Li, LY (Li, Linyuan)[ 1 ] ; Qi, JB (Qi, Jianbo)[ 1 ] ; Wang, XY (Wang, Xiaoyan)[ 1 ] ; Luo, JH (Luo, Jinghui)[ 1 ] ; Chu, Q (Chu, Qing)[ 1 ]

OPTICS EXPRESS

卷: 23  期: 6  页: 7694-7702

DOI: 10.1364/OE.23.007694

出版年: MAR 23 2015

摘要

A novel method for registering imagery with Light Detection And Ranging (LiDAR) data is proposed. It is based on the phenomenon that the back-projection of LiDAR point cloud of an object should be located within the object boundary in the image. Using this inherent geometrical constraint, the registration parameters computation of both data sets only requires LiDAR point clouds of several objects and their corresponding boundaries in the image. The proposed registration method comprises of four steps: point clouds extraction, boundary extraction, back-projection computation and registration parameters computation. There are not any limitations on the geometrical and spectral properties of the object. So it is suitable not only for structured scenes with man-made objects but also for natural scenes. Moreover, the proposed method based on the inherent geometrical constraint can register two data sets derived from different parts of an object. It can be used to co-register TLS (Terrestrial Laser Scanning) LiDAR point cloud and UAV (Unmanned aerial vehicle) image, which are obtaining more attention in the forest survey application. Using initial registration parameters comparable to POS (position and orientation system) accuracy, the performed experiments validated the feasibility of the proposed registration method. (C) 2015 Optical Society of America

通讯作者地址: Zhang, WM (通讯作者)

Beijing Normal Univ, Sch Geog, Beijing Key Lab Environm Remote Sensing & Digital, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China.

地址:

[ 1 ] Beijing Normal Univ, Sch Geog, Beijing Key Lab Environm Remote Sensing & Digital, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China