Geometric registration of close-range optical image and terrestrial laser point cloud constrained by nearest surface

doi:10.11947/j.AGCS.2020.20190146

Abstract

Abstract: In this paper, a high-precision registration method based on the nearest surface for close-range optical image and terrestrial laser point cloud is proposed.Three-dimensional sparse point cloud is generated from optical images. Constrained by the local surface fitted by the laser points adjacent to the 3D sparse point of the image, a transformation model between the three-dimensional sparse point cloud and the three-dimensional laser point cloud is constructed by using collinear conditional equation. The high precision geometric registration of optical images and the laser point cloud is completed by iterative calculation. The method only needs initial registration parameter and does not need to perform feature extraction and segmentation on the laser point cloud data. In addition, the problem that it is difficult to accurately determine the correspondence points between two sets of points is solved effectively based on the surface constraint. The results of two sets of experimental data show that this method can effectively improve the accuracy of rigid registration algorithm, and can achieve higher registration accuracy.

Key words: nearest surface, optical image, laser point cloud, geometric registration

CLC Number:

P227

LI Cailin, WANG Zhiyong, YU Lulu, GUO Baoyun. Geometric registration of close-range optical image and terrestrial laser point cloud constrained by nearest surface[J]. Acta Geodaetica et Cartographica Sinica, 2020, 49(8): 1014-1022.

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