PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Learning High-Order MRF Priors of Color Image
J. McAuley, T. Caetano, Alex Smola and Matthias Franz
In: 23rd Intl. Conf. Machine Learning (ICML 2006), Pittsburg, USA(2006).


In this paper, we use large neighborhood Markov random fields to learn rich prior models of color images. Our approach extends the monochromatic Fields of Experts model (Roth and Blackwell, 2005} to color images. In the Fields of Experts model, the curse of dimensionality due to very large clique sizes is circumvented by parameterizing the potential functions according to a product of experts. We introduce several simplifications of the original approach by Roth and Black which allow us to cope with the increased clique size (typically 3x3x3 or 5x5x3 pixels) of color images. Experimental results are presented for image denoising which evidence improvements over state-of-the-art monochromatic image priors.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Machine Vision
Learning/Statistics & Optimisation
ID Code:2317
Deposited By:Matthias Franz
Deposited On:19 November 2006