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Applied Optics

Applied 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)

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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

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

Esteban Vera, Miguel Vega, Rafael Molina, and Aggelos K. Katsaggelos, "Iterative image restoration using nonstationary priors," Appl. Opt. 52, D102-D110 (2013)

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