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Proceedings Paper

Coarse-to-fine geometric and photometric image registration
Author(s): Jieping Xu; Jin Liu; Zongfu Huang; Yonghui Liang
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Paper Abstract

This paper presents a technique that performs coarse-to-fine image registration both in spatial and range domain. The goal of image registration is to estimate geometric and photometric parameters via minimization of an objective function in the least square sense. In order to reduce the probability of falling into a local optimal solution, the algorithm employs a coarse-to-fine strategy. In the coarse step, an illumination offset and contrast invariant feature detector which is named SURF is used to estimate affine motion parameters between the reference image and the target image, and then the intensity of corresponding pixels is used to directly estimate contrast and bias parameters based on RANSAC. In the fine step, the estimated parameters obtained in the coarse step are used as a good initial estimation, and photometric and affine motion parameters are refined alternatively via minimizing the objective function. Experiments on simulated and real images show that the proposed image registration method is superior to the feature-based method used in the coarse step and the groupwise image registration algorithm proposed by Bartoli.

Paper Details

Date Published: 24 October 2017
PDF: 7 pages
Proc. SPIE 10462, AOPC 2017: Optical Sensing and Imaging Technology and Applications, 1046202 (24 October 2017); doi: 10.1117/12.2281123
Show Author Affiliations
Jieping Xu, National Univ. of Defense Technology (China)
Jin Liu, National Univ. of Defense Technology (China)
Zongfu Huang, National Univ. of Defense Technology (China)
Yonghui Liang, National Univ. of Defense Technology (China)

Published in SPIE Proceedings Vol. 10462:
AOPC 2017: Optical Sensing and Imaging Technology and Applications
Yadong Jiang; Haimei Gong; Weibiao Chen; Jin Li, Editor(s)

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