Department of Mathematics
 Search | Help | Login | pdf version | printable version

Math @ Duke



Publications [#265043] of Guillermo Sapiro

Papers Published

  1. Arias, P; Caselles, V; Sapiro, G, A variational framework for non-local image inpainting, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5681 LNCS (2009), pp. 345-358, ISSN 0302-9743 [doi]
    (last updated on 2018/10/16)

    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 structure 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 for the problem of non-local image inpainting, from which several 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. © 2009 Springer.
ph: 919.660.2800
fax: 919.660.2821

Mathematics Department
Duke University, Box 90320
Durham, NC 27708-0320