Camera Self-calibration Method Based on Large Scale Aerial Images Coplanarity Constraint

doi:10.11947/j.AGCS.2017.20160206

Abstract

Abstract: In this paper an automated camera self-calibration method based on large scale aerial images coplanarity constraint is proposed. The method uses stereo images corresponding points to compute camera inner parameters and the distortion coefficients based on coplanarity constraint. Firstly, aerial images corresponding points are matched and stereo images are constructed. Then the relative orientation of the camera is resolved by using the direct method and the iterative optimization based on the coplanarity constraint. Finally, the least square optimization method is used to calculate the inner parameters and the distortion coefficients of the camera. For large image the distortion of image boundary is more severe than center, in order to compute parameters more precisely mesh partition in arbitrary area of image is proposed. Compared with classical techniques which use expensive equipment or calibration field, the proposed technique can reflect the actual inner parameters of the camera in the real environment. Using all the corresponding points avoid the influence of choosing different feature points or control points on the calibration accuracy.Experimental results indicate that it is effective and flexible.The accuracy of the method is equivalent to that of calibration field, which can accurately reflect the camera parameters and the distortion coefficients of the image acquired by aerial photogrammetry.

Key words: large scale aerial image, coplanarity constraint, camera self-calibration, mesh partition

CLC Number:

P235

ZHAO Shuang, LI Xuejun, LIU Tao, XIE Jianwei. Camera Self-calibration Method Based on Large Scale Aerial Images Coplanarity Constraint[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(1): 98-106.

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