Skip to Main content Skip to Navigation
Journal articles

Posterior Expectation of the Total Variation model: Properties and Experiments

Abstract : The Total Variation image (or signal) denoising model is a variational approach that can be interpreted, in a Bayesian framework, as a search for the maximum point of the posterior density (Maximum A Posteriori estimator). This maximization aspect is partly responsible for a restoration bias called ''staircasing effect'', that is, the outbreak of quasi-constant regions separated by sharp edges in the intensity map. In this paper we study a variant of this model that considers the expectation of the posterior distribution instead of its maximum point. Apart from the least square error optimality, this variant seems to better account for the global properties of the posterior distribution. Theoretical and numerical results are presented, that demonstrate in particular that images denoised with this model do not suffer from the staircasing effect.
Complete list of metadata

Cited literature [74 references]  Display  Hide  Download
Contributor : Cécile Louchet <>
Submitted on : Monday, April 27, 2015 - 4:55:38 PM
Last modification on : Friday, April 10, 2020 - 5:01:03 PM
Long-term archiving on: : Monday, September 14, 2015 - 2:07:25 PM


Publisher files allowed on an open archive



Cécile Louchet, Lionel Moisan. Posterior Expectation of the Total Variation model: Properties and Experiments. SIAM Journal on Imaging Sciences, Society for Industrial and Applied Mathematics, 2013, 6 (4), pp.2640-2684. ⟨10.1137/120902276⟩. ⟨hal-00764175v3⟩



Record views


Files downloads