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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editor: Gregory W. Faris
  • Vol. 2, Iss. 5 — May. 17, 2007

Robust and computationally efficient superresolution algorithm

Kaggere V. Suresh and Ambasamudram N. Rajagopalan  »View Author Affiliations


JOSA A, Vol. 24, Issue 4, pp. 984-992 (2007)
http://dx.doi.org/10.1364/JOSAA.24.000984


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Abstract

Superresolution is the process of combining information from multiple subpixel-shifted low-resolution images to form a high-resolution image. It works quite well under ideal conditions but deteriorates rapidly with inaccuracies in motion estimates. We model the original high-resolution image as a Markov random field (MRF) with a discontinuity adaptive regularizer. Given the low-resolution observations, an estimate of the superresolved image is obtained by using the iterated conditional modes (ICM) algorithm, which maximizes the local posterior conditional probability sequentially. The proposed method not only preserves edges but also lends robustness to errors in the estimates of motion and blur parameters. We derive theoretically the neighborhood structure for the posterior distribution in the presence of warping, blurring, and downsampling operations and use this to effectively reduce the overall computations. Results are given on synthetic as well as real data to validate our method.

© 2007 Optical Society of America

OCIS Codes
(100.3010) Image processing : Image reconstruction techniques
(100.6640) Image processing : Superresolution

ToC Category:
Image Processing

History
Original Manuscript: May 5, 2006
Revised Manuscript: August 14, 2006
Manuscript Accepted: October 9, 2006
Published: March 14, 2007

Virtual Issues
Vol. 2, Iss. 5 Virtual Journal for Biomedical Optics

Citation
Kaggere V. Suresh and Ambasamudram N. Rajagopalan, "Robust and computationally efficient superresolution algorithm," J. Opt. Soc. Am. A 24, 984-992 (2007)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=josaa-24-4-984


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