Accession Number : ADA540639


Title :   A Variational Framework for Exemplar-Based Image Inpainting


Corporate Author : MINNESOTA UNIV MINNEAPOLIS INST FOR MATHEMATICS AND ITS APPLICATIONS


Personal Author(s) : Arias, Pablo ; Facciolo, Gabriele ; Caselles, Vicent ; Sapiro, Guillermo


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a540639.pdf


Report Date : Apr 2010


Pagination or Media Count : 27


Abstract : Non-local methods for image denoising and inpainting have gained considerable attention in recent years. This is in part due to their superior performance in textured images, a known weakness of purely local methods. Local methods on the other hand have demonstrated to be very appropriate for the recovering of geometric structures such as image edges. The synthesis of both types of methods is a trend in current research. Variational analysis in particular is an appropriate tool for a unified treatment of local and non-local methods. In this work we propose a general variational framework non-local image inpainting, from which important and representative previous inpainting schemes can be derived, in addition to leading to novel ones. We explicitly study some of these, relating them to previous work and showing results on synthetic and real images.


Descriptors :   *IMAGES , *VARIATIONAL METHODS , *MATHEMATICS , *PARTIAL DIFFERENTIAL EQUATIONS , SYNTHETIC MATERIALS , TEXTURE , GEOMETRIC FORMS , STRUCTURES , SYNTHESIS , ALGORITHMS


Subject Categories : Numerical Mathematics


Distribution Statement : APPROVED FOR PUBLIC RELEASE