Diffusion-based spatial priors for imaging
We describe a Bayesian scheme to analyze images, which uses spatial priors encoded by a diffusion kernel, based on a weighted graph Laplacian. This provides a general framework to formulate a spatial model, whose parameters can be optimised. The standard practice using the software statistical param...
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University College London (University of London)
2008
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| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.631787 |