Adaptive regularization of the NL-means : Application to image and video denoising

Abstract : Image denoising is a central problem in image processing and it is often a necessary step prior to higher level analysis such as segmentation, reconstruction or super-resolution. The non-local means (NL-means) perform denoising by exploiting the natural redundancy of patterns inside an image; they perform a weighted average of pixels whose neighborhoods (patches) are close to each other. This reduces significantly the noise while preserving most of the image content. While it performs well on flat areas and textures, it suffers from two opposite drawbacks: it might over-smooth low-contrasted areas or leave a residual noise around edges and singular structures. Denoising can also be performed by total variation minimization -- the ROF model -- which leads to restore regular images, but it is prone to over-smooth textures, staircasing effects, and contrast losses. We introduce in this paper a variational approach that corrects the over-smoothing and reduces the residual noise of the NL-means by adaptively regularizing non-local methods with the total variation. The proposed regularized NL-means algorithm combines these methods and reduces both of their respective defaults by minimizing an adaptive total variation with a non-local data fidelity term. Besides, this model adapts to different noise statistics and a fast solution can be obtained in the general case of the exponential family. We develop this model for image denoising and we adapt it to video denoising with 3D patches.
Type de document :
Article dans une revue
IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2014, <10.1109/TIP.2014.2329448>
Liste complète des métadonnées


https://hal.archives-ouvertes.fr/hal-00854830
Contributeur : Camille Sutour <>
Soumis le : lundi 2 juin 2014 - 15:43:17
Dernière modification le : jeudi 3 décembre 2015 - 01:04:40
Document(s) archivé(s) le : mardi 2 septembre 2014 - 12:35:36

Fichier

IP.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Camille Sutour, Charles-Alban Deledalle, Jean-François Aujol. Adaptive regularization of the NL-means : Application to image and video denoising. IEEE Transactions on Image Processing, Institute of Electrical and Electronics Engineers, 2014, <10.1109/TIP.2014.2329448>. <hal-00854830v3>

Partager

Métriques

Consultations de
la notice

744

Téléchargements du document

952