OSA's Digital Library

Applied Optics

Applied Optics

APPLICATIONS-CENTERED RESEARCH IN OPTICS

  • Editor: Joseph N. Mait
  • Vol. 52, Iss. 10 — Apr. 1, 2013
  • pp: D102–D110

Iterative image restoration using nonstationary priors

Esteban Vera, Miguel Vega, Rafael Molina, and Aggelos K. Katsaggelos  »View Author Affiliations


Applied Optics, Vol. 52, Issue 10, pp. D102-D110 (2013)
http://dx.doi.org/10.1364/AO.52.00D102


View Full Text Article

Enhanced HTML    Acrobat PDF (808 KB)





Browse Journals / Lookup Meetings

Browse by Journal and Year


   


Lookup Conference Papers

Close Browse Journals / Lookup Meetings

Article Tools

Share
Citations

Abstract

In this paper, we propose an algorithm for image restoration based on fusing nonstationary edge-preserving priors. We develop a Bayesian modeling followed by an evidence approximation inference approach for deriving the analytic foundations of the proposed restoration method. Through a series of approximations, the final implementation of the proposed image restoration algorithm is iterative and takes advantage of the Fourier domain. Simulation results over a variety of blurred and noisy standard test images indicate that the presented method comfortably surpasses the current state-of-the-art image restoration for compactly supported degradations. We finally present experimental results by digitally refocusing images captured with controlled defocus, successfully confirming the ability of the proposed restoration algorithm in recovering extra features and rich details, while still preserving edges.

© 2013 Optical Society of America

OCIS Codes
(100.1830) Image processing : Deconvolution
(100.3020) Image processing : Image reconstruction-restoration
(100.3190) Image processing : Inverse problems
(110.3010) Imaging systems : Image reconstruction techniques

History
Original Manuscript: November 16, 2012
Revised Manuscript: February 11, 2013
Manuscript Accepted: February 11, 2013
Published: March 29, 2013

Citation
Esteban Vera, Miguel Vega, Rafael Molina, and Aggelos K. Katsaggelos, "Iterative image restoration using nonstationary priors," Appl. Opt. 52, D102-D110 (2013)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-52-10-D102


Sort:  Author  |  Year  |  Journal  |  Reset  

References

  1. M. Banham and A. Katsaggelos, “Digital image restoration,” IEEE Signal Process. Mag. 14(2), 24–41 (1997). [CrossRef]
  2. H. C. Andrews and B. R. Hunt, Digital Image Restoration (Prentice-Hall, 1977).
  3. M. Bertero and P. Boccacci, Introduction to Inverse Problems in Imaging (Taylor & Francis, 1998).
  4. A. Katsaggelos, S. Babacan, and C.-J. Tsai, “Iterative image restoration,” in The Essential Guide to Image Processing, A. Bovik, ed. (Elsevier, 2009), Chap. 15.
  5. R. Molina, “On the hierarchical Bayesian approach to image restoration: applications to astronomical images,” IEEE Trans. Pattern Anal. Mach. Intell. 16, 1122–1128 (1994). [CrossRef]
  6. R. Molina, A. Katsaggelos, and J. Mateos, “Bayesian and regularization methods for hyperparameter estimation in image restoration,” IEEE Trans. Image Process. 8, 231–246 (1999). [CrossRef]
  7. D. Tzikas, A. Likas, and N. Galatsanos, “The variational approximation for Bayesian inference,” IEEE Signal Process. Mag. 25(6), 131–146 (2008). [CrossRef]
  8. S. Babacan, R. Molina, and A. Katsaggelos, “Parameter estimation in tv image restoration using variational distribution approximation,” IEEE Trans. Image Process. 17, 326–339 (2008). [CrossRef]
  9. R. Fergus, B. Singh, A. Hertzmann, S. T. Roweis, and W. T. Freeman, “Removing camera shake from a single photograph,” ACM Trans. Graph. 25, 787–794 (2006). [CrossRef]
  10. G. Chantas, N. Galatsanos, A. Likas, and M. Saunders, “Variational Bayesian image restoration based on a product of t-distributions image prior,” IEEE Trans. Image Process. 17, 1795–1805 (2008). [CrossRef]
  11. G. Chantas, N. Galatsanos, R. Molina, and A. Katsaggelos, “Variational Bayesian image restoration with a product of spatially weighted total variation image priors,” IEEE Trans. Image Process. 19, 351–362 (2010). [CrossRef]
  12. G. Chantas, N. Galatsanos, and A. Likas, “Bayesian restoration using a new nonstationary edge-preserving image prior,” IEEE Trans. Image Process. 15, 2987–2997 (2006). [CrossRef]
  13. S. Roth and M. J. Black, “Fields of experts,” Int. J. Comput. Vis. 82, 205–229 (2009). [CrossRef]
  14. S. Babacan, R. Molina, M. Do, and A. Katsaggelos, “Blind deconvolution with general sparse image priors,” in Proceedings of European Conference on Computer Vision (ECCV) (Springer, 2012), pp. 341–355.
  15. R. Molina, J. Mateos, and A. Katsaggelos, “Blind deconvolution using a variational approach to parameter, image, and blur estimation,” IEEE Trans. Image Process. 15, 3715–3727 (2006). [CrossRef]

Cited By

Alert me when this paper is cited

OSA is able to provide readers links to articles that cite this paper by participating in CrossRef's Cited-By Linking service. CrossRef includes content from more than 3000 publishers and societies. In addition to listing OSA journal articles that cite this paper, citing articles from other participating publishers will also be listed.


« Previous Article

OSA is a member of CrossRef.

CrossCheck Deposited