Centre de Mathématiques et de Leurs Applications

Orateur : Jérôme Darbon (UCLA)

Titre :

Combinatorial and parallel programming point of views for
Markovian Energies Minimization

Résumé :

Many image processing processing problems can be formulated as the
minimization of a Markovian energy. In this talk, a combinatorial point
of view is considered. I focus on the minimization of the Total
Variation with convex data fidelity terms both from a continuous and a
discrete point of view. Two algorithms are presented: a) a pure
combinatorial algorithm relying on the parametric maximum-flow in
a network. and b) an approximation algorithm that allows an extremely
efficient parallel programming implementation. Several applications
such as crystalline mean curvature flow, deconvolution and compressive
sensing reconstruction are also presented.







Quoting Kar