ESTIMATING FIRST-ORDER FINITE-DIFFERENCE INFORMATION IN IMAGE RESTORATION PROBLEMS (MA-P3)

Author(s) : Patrick L. Combettes (Universite Paris 6, France) Jean-Christophe Pesquet (Universite Marne la Vallee, France)

Abstract : First-order finite-difference information has been exploited in a variety of image and signal restoration settings. These approaches typically require -- implicitly or explicitly -- that certain attributes of the finite difference images be known a priori. In this paper, we propose a new statistical framework in which such attributes are estimated a posteriori from the observed data. The proposed approach is applicable to models involving additive Gaussian noise and it leads to geometrically simple sets that can easily be handled via projection methods. An application to image denoising is demonstrated.

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