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  • Title: Variational bayesian blind deconvolution using a total variation prior.
    Author: Babacan SD, Molina R, Katsaggelos AK.
    Journal: IEEE Trans Image Process; 2009 Jan; 18(1):12-26. PubMed ID: 19095515.
    Abstract:
    In this paper, we present novel algorithms for total variation (TV) based blind deconvolution and parameter estimation utilizing a variational framework. Using a hierarchical Bayesian model, the unknown image, blur, and hyperparameters for the image, blur, and noise priors are estimated simultaneously. A variational inference approach is utilized so that approximations of the posterior distributions of the unknowns are obtained, thus providing a measure of the uncertainty of the estimates. Experimental results demonstrate that the proposed approaches provide higher restoration performance than non-TV-based methods without any assumptions about the unknown hyperparameters.
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