SSP'05 -- Proceedings

	IEEE/SP 13th workshop on Statistical Signal Processing July, 17-20, 2005 - Bordeaux - France

Information regarding the paper

Title

A Bayesian approach to nonlinear diffusion based on a Laplacian prior for ideal image gradient

Author(s)

Aleksandra Pizurica	Universiteit Gent /Vakgroep TELIN
Iris Vanhamel	Vrije Universiteit Brussel (ETRO)
Hichem Sahli	Vrije Universiteit Brussel (ETRO)
Wilfried Philips	Universiteit Gent /Vakgroep TELIN
Antonis Katartzis	Vrije Universiteit Brussel (ETRO)

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Abstract

We study the relationships between diffusivity functions in a nonlinear diffusion scheme and probabilities of edge presence under a marginal prior on ideal, noise-free image gradient. In particular we impose a Laplacian-shaped prior for the ideal gradient and we define the diffusivity function explicitly in terms of edge probabilities under this prior. The resulting diffusivity function has no free parameters to optimize. Our results demonstrate that the new diffusivity function, automatically, i.e., without any parameter adjustments, satisfies the well accepted criteria for the goodness of edge-stopping functions. Our results also offer a new and interesting interpretation of some widely used diffusivity functions, which are now compared to edge-stopping functions under a marginal prior for the ideal image gradient.