Automatic Registration of Terrestrial Laser Scanning Point Clouds using Panoramic Reflectance Images

Sensors

Zhizhong Kang²  Jonathan Li⁴  Liqiang Zhang¹  Qile Zhao³ 

[1] Research Centre for Remote Sensing and GIS, School of Geography, Beijing Normal University / Beijing 100875, P.R. China; E-Mail:;Faculty of Aerospace Engineering, Delft University of Technology / Kluyverweg 1, 2629 HS Delft, The Netherlands;GNSS Research Centre, Wuhan University / Wuhan 430079, Hubei Province, P.R. China; E-Mail:;Department of Geography and Environmental Management, University of Waterloo / Waterloo, Ontario N2L 3G1, Canada; E-Mail:

关键词: Point cloud;    Registration;    LIDAR;    Terrestrial laser scanning;    Automation;    Image Matching;   

DOI  :  10.3390/s90402621

来源: mdpi

【 摘 要 】

This paper presents a new approach to the automatic registration of terrestrial laser scanning (TLS) point clouds using panoramic reflectance images. The approach follows a two-step procedure that includes both pair-wise registration and global registration. The pair-wise registration consists of image matching (pixel-to-pixel correspondence) and point cloud registration (point-to-point correspondence), as the correspondence between the image and the point cloud (pixel-to-point) is inherent to the reflectance images. False correspondences are removed by a geometric invariance check. The pixel-to-point correspondence and the computation of the rigid transformation parameters (RTPs) are integrated into an iterative process that allows for the pair-wise registration to be optimised. The global registration of all point clouds is obtained by a bundle adjustment using a circular self-closure constraint. Our approach is tested with both indoor and outdoor scenes acquired by a FARO LS 880 laser scanner with an angular resolution of 0.036° and 0.045°, respectively. The results show that the pair-wise and global registration accuracies are of millimetre and centimetre orders, respectively, and that the process is fully automatic and converges quickly.

【 授权许可】

CC BY   
© 2009 by the authors; licensee MDPI, Basel, Switzerland