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Consistent joint photometric and geometric image registration

Hiep Luong (UGent) , Bart Goossens (UGent) , Aleksandra Pizurica (UGent) and Wilfried Philips (UGent)
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Abstract
In this paper, we derive a novel robust image alignment technique that performs joint geometric and photometric registration in the total least square sense. The main idea is to use the total least square metrics instead of the ordinary least square metrics, which is commonly used in the literature. While the OLS model indicates that the target image may contain noise and the reference image should be noise-free, this puts a severe limitation on practical registration problems. By introducing the TLS model, which allows perturbations in both images, we can obtain mutually consistent parameters. Experimental results show that our method is indeed much more consistent and accurate in presence of noise compared to existing registration algorithms.
Keywords
total least square, Photometric and geometric image registration, orthogonal distance regression, CAMERA RESPONSE

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Citation

Please use this url to cite or link to this publication:

Chicago
Luong, Hiep, Bart Goossens, Aleksandra Pizurica, and Wilfried Philips. 2010. “Consistent Joint Photometric and Geometric Image Registration.” In IEEE International Conference on Image Processing ICIP, 1197–1200. New York, NY, USA: IEEE.
APA
Luong, Hiep, Goossens, B., Pizurica, A., & Philips, W. (2010). Consistent joint photometric and geometric image registration. IEEE International Conference on Image Processing ICIP (pp. 1197–1200). Presented at the 2010 IEEE 17th International conference on Image Processing (ICIP 2010), New York, NY, USA: IEEE.
Vancouver
1.
Luong H, Goossens B, Pizurica A, Philips W. Consistent joint photometric and geometric image registration. IEEE International Conference on Image Processing ICIP. New York, NY, USA: IEEE; 2010. p. 1197–200.
MLA
Luong, Hiep, Bart Goossens, Aleksandra Pizurica, et al. “Consistent Joint Photometric and Geometric Image Registration.” IEEE International Conference on Image Processing ICIP. New York, NY, USA: IEEE, 2010. 1197–1200. Print.
@inproceedings{1062169,
  abstract     = {In this paper, we derive a novel robust image alignment technique that performs joint geometric and photometric registration in the total least square sense. The main idea is to use the total least square metrics instead of the ordinary least square metrics, which is commonly used in the literature. While the OLS model indicates that the target image may contain noise and the reference image should be noise-free, this puts a severe limitation on practical registration problems. By introducing the TLS model, which allows perturbations in both images, we can obtain mutually consistent parameters. Experimental results show that our method is indeed much more consistent and accurate in presence of noise compared to existing registration algorithms.},
  author       = {Luong, Hiep and Goossens, Bart and Pizurica, Aleksandra and Philips, Wilfried},
  booktitle    = {IEEE International Conference on Image Processing ICIP},
  isbn         = {9781424479931},
  issn         = {1522-4880},
  language     = {eng},
  location     = {Hong Kong, PR China},
  pages        = {1197--1200},
  publisher    = {IEEE},
  title        = {Consistent joint photometric and geometric image registration},
  year         = {2010},
}

Web of Science
Times cited: