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Generalized Gaussian Markov random field image restoration using variational distribution approximation

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3 Author(s)
S. Derin Babacan ; Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL 60208, USA ; Rafael Molina ; Aggelos K. Katsaggelos

In this paper we propose novel algorithms for image restoration and parameter estimation with a generalized Gaussian Markov random field (GGMRF) prior utilizing variational distribution approximation. The restored image and the unknown hyperparameters for both the image prior and the image degradation noise are simultaneously estimated within a hierarchical Bayesian framework. We develop two algorithms resulting from this formulation which provide approximations to the posterior distributions of the latent variables. Experimental results are provided to demonstrate the performance of the algorithms.

Published in:

2008 IEEE International Conference on Acoustics, Speech and Signal Processing

Date of Conference:

March 31 2008-April 4 2008