Convex half-quadratic criteria and interacting auxiliary variables for image restoration.
This paper deals with convex half-quadratic criteria and associated minimization algorithms for the purpose of image restoration. It brings a number of original elements within a unified mathematical presentation based on convex duality. Firstly, the Geman and Yang's and Geman and Reynolds's constructions are revisited, with a view to establishing the convexity properties of the resulting half-quadratic augmented criteria, when the original nonquadratic criterion is already convex. Secondly, a family of convex Gibbsian energies that incorporate interacting auxiliary variables is revealed as a potentially fruitful extension of the Geman and Reynolds's construction.
Idier
J
J
Laboratoire des Signaux et Systèmes (CNRS-SUPELECUPS), 91192 Gif-sur-Yvette Cedex, France. idier@lss.supelec.fr