Non-Rigid Registration of Images With Geometric and Photometric Deformation by Using Local Affine Fourier-Moment Matching

Hong-Ren Su, Shang-Hong Lai; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 2874-2882

Abstract


Registration between images taken with different cameras, from different viewpoints or under different lighting conditions is a challenging problem. It needs to solve not only the geometric registration problem but also the photometric matching problem. In this paper, we propose to estimate the integrated geometric and photometric transformations between two images based on a local affine Fourier-moment matching framework, which is developed to achieve deformable registration. We combine the local Fourier moment constraints with the smoothness constraints to determine the local affine transforms in a hierarchal block model. Our experimental results on registering some real images related by large color and geometric transformations show the proposed registration algorithm provides superior image registration results compared to the state-of-the-art image registration methods.

Related Material


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[bibtex]
@InProceedings{Su_2015_CVPR,
author = {Su, Hong-Ren and Lai, Shang-Hong},
title = {Non-Rigid Registration of Images With Geometric and Photometric Deformation by Using Local Affine Fourier-Moment Matching},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}