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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics


  • Editors: Andrew Dunn and Anthony Durkin
  • Vol. 7, Iss. 3 — Feb. 29, 2012

Robust visual correspondence computation using monogenic curvature phase based mutual information

Di Zang, Jie Li, and Dongdong Zhang  »View Author Affiliations

Optics Letters, Vol. 37, Issue 1, pp. 10-12 (2012)

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Visual correspondence has been a major research topic in the fields of image registration, 3D reconstruction, and object tracking for some decades. However, due to the radiometric variations of images, conventional approaches fail to produce robust matching results. The traditional method of intensity-based mutual information performs very good for global variations between images, however, its performance degrades in the case of local radiometric variations. Monogenic curvature phase information, as an important local feature of the image, has the advantage of being robust against brightness variation. Hence, in this Letter, we propose an approach to compute the visual correspondence by coupling the advantages of mutual information and monogenic curvature phase. Experimental results demonstrate that the proposed approach can work robustly under radiometric variations.

© 2012 Optical Society of America

OCIS Codes
(100.2000) Image processing : Digital image processing
(100.2960) Image processing : Image analysis
(330.1400) Vision, color, and visual optics : Vision - binocular and stereopsis
(100.3008) Image processing : Image recognition, algorithms and filters

ToC Category:
Image Processing

Original Manuscript: August 1, 2011
Revised Manuscript: October 30, 2011
Manuscript Accepted: October 31, 2011
Published: December 22, 2011

Virtual Issues
Vol. 7, Iss. 3 Virtual Journal for Biomedical Optics

Di Zang, Jie Li, and Dongdong Zhang, "Robust visual correspondence computation using monogenic curvature phase based mutual information," Opt. Lett. 37, 10-12 (2012)

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