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IEEE Trans Image Process. 2008 Mar;17(3):326-39. doi: 10.1109/TIP.2007.916051.

Parameter estimation in TV image restoration using variational distribution approximation.

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  • 1Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL 60208-3118, USA.


In this paper, we propose novel algorithms for total variation (TV) based image restoration and parameter estimation utilizing variational distribution approximations. Within the hierarchical Bayesian formulation, the reconstructed image and the unknown hyper parameters for the image prior and the noise are simultaneously estimated. The proposed algorithms provide approximations to the posterior distributions of the latent variables using variational methods. We show that some of the current approaches to TV-based image restoration are special cases of our framework. Experimental results show that the proposed approaches provide competitive performance without any assumptions about unknown hyper parameters and clearly outperform existing methods when additional information is included.

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