26 October 2013 A robust correspondence matching algorithm of ground images along the optic axis
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Proceedings Volume 8918, MIPPR 2013: Automatic Target Recognition and Navigation; 89181A (2013) https://doi.org/10.1117/12.2031394
Event: Eighth International Symposium on Multispectral Image Processing and Pattern Recognition, 2013, Wuhan, China
Abstract
Facing challenges of nontraditional geometry, multiple resolutions and the same features sensed from different angles, there are more difficulties of robust correspondence matching for ground images along the optic axis.
A method combining SIFT algorithm and the geometric constraint of the ratio of coordinate differences between image point and image principal point is proposed in this paper. As it can provide robust matching across a substantial range of affine distortion addition of change in 3D viewpoint and noise, we use SIFT algorithm to tackle the problem of image distortion. By analyzing the nontraditional geometry of ground image along the optic axis, this paper derivates that for one correspondence pair, the ratio of distances between image point and image principal point in an image pair should be a value not far from 1. Therefore, a geometric constraint for gross points detection is formed. The proposed approach is tested with real image data acquired by Kodak. The results show that with SIFT and the proposed geometric constraint, the robustness of correspondence matching on the ground images along the optic axis can be effectively improved, and thus prove the validity of the proposed algorithm.
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Fengman Jia, Fengman Jia, Zhizhong Kang, Zhizhong Kang, } "A robust correspondence matching algorithm of ground images along the optic axis", Proc. SPIE 8918, MIPPR 2013: Automatic Target Recognition and Navigation, 89181A (26 October 2013); doi: 10.1117/12.2031394; https://doi.org/10.1117/12.2031394
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