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Nonlocal video denoising, simplification and inpainting using discrete regularization on graphs

Mahmoud Ghoniem 1 Youssef Chahir 1 Abderrahim Elmoataz 1
1 Equipe Image - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
Abstract : We present nonlocal algorithms for video denoising, simplification and inpainting based on a generic framework of discrete regularization on graphs. We express video denoising, simplification and inpainting problems using the same variational formulation. The main advantage of this framework is the unification of local and nonlocal approaches for these processing procedures. We take advantage of temporal and spatial redundancies in order to produce high quality results. In this paper, we consider a video sequence as a volume rather than a sequence of frames, and employ algorithms that do not require any motion estimation. For video inpainting, we unify geometric- and texture-synthesis-based approaches. To reduce the computational effort, we propose an optimized method that is faster than the nonlocal approach, while producing equally appealing results.
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https://hal.archives-ouvertes.fr/hal-00812354
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Submitted on : Friday, April 12, 2013 - 9:21:52 AM
Last modification on : Wednesday, November 13, 2019 - 3:41:37 PM

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Mahmoud Ghoniem, Youssef Chahir, Abderrahim Elmoataz. Nonlocal video denoising, simplification and inpainting using discrete regularization on graphs. Signal Processing, Elsevier, 2010, 90 (8), pp.2445-2455. ⟨10.1016/j.sigpro.2009.09.004⟩. ⟨hal-00812354⟩

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