Acta Geodaetica et Cartographica Sinica ›› 2015, Vol. 44 ›› Issue (5): 518-525.doi: 10.11947/j.AGCS.2015.20130558

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Automatic Registration of Low Altitude UAV Sequent Images and Laser Point Clouds

CHEN Chi1,2, YANG Bisheng1,2, PENG Xiangyang3   

  1. 1. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
    2. Engineering Research Center for Spatio-temporal Data Smart Acquisition and Application, Ministry of Education of China, Wuhan University, Wuhan 430079, China;
    3. Guangdong Electric Power Research Institute, Guangzhou 510080, China
  • Received:2013-11-08 Revised:2014-05-05 Online:2015-05-20 Published:2015-05-27
  • Supported by:

    The National Natural Science Foundation of China (No. 41371431);The National Basic Research Program of China(973 Program)(No. 2012CB725301);Doctoral Scientific Fund Project of the Ministry of Education of China(No.20120141110035);Southern Power Grid Company Funded Key Research Program(No.K-GD2013-030)

Abstract:

It is proposed that a novel registration method for automatic co-registration of unmanned aerial vehicle (UAV) images sequence and laser point clouds. Firstly, contours of building roofs are extracted from the images sequence and laser point clouds using marked point process and local salient region detection, respectively. The contours from each data are matched via back-project proximity. Secondly, the exterior orientations of the images are recovered using a linear solver based on the contours corner pairs followed by a co-planar optimization which is implicated by the matched lines form contours pairs. Finally, the exterior orientation parameters of images are further optimized by matching 3D points generated from images sequence and laser point clouds using an iterative near the point (ICP) algorithm with relative movement threshold constraint. Experiments are undertaken to check the validity and effectiveness of the proposed method. The results show that the proposed method achieves high-precision co-registration of low-altitude UAV image sequence and laser points cloud robustly. The accuracy of the co-produced DOMs meets 1:500 scale standards.

Key words: airborne LiDAR point cloud, UAV image sequences, registration, UAV

CLC Number: