title: 3D wavelet subbands mixing for image denoising.
abstract: A critical issue in image restoration is the problem of noise removal while keeping the integrity of relevant image information. The method proposed in this paper is a fully automatic 3D blockwise version of the nonlocal (NL) means filter with wavelet subbands mixing. The proposed wavelet subbands mixing is based on a multiresolution approach for improving the quality of image denoising filter. Quantitative validation was carried out on synthetic datasets generated with the BrainWeb simulator. The results show that our NL-means filter with wavelet subbands mixing outperforms the classical implementation of the NL-means filter in terms of denoising quality and computation time. Comparison with wellestablished methods, such as nonlinear diffusion filter and total variation minimization, shows that the proposed NL-means filter produces better denoising results. Finally, qualitative results on real data are presented.
authors.affiliation: University of Rennes I, CNRS UMR 6074, IRISA, F-35042 Rennes, France. pierrick.coupe@irisa.fr
authors.forename: Pierrick
authors.initials: P
authors.lastname: Coupé
authors.forename: Pierre
authors.initials: P
authors.lastname: Hellier
authors.forename: Sylvain
authors.initials: S
authors.lastname: Prima
authors.forename: Charles
authors.initials: C
authors.lastname: Kervrann
authors.forename: Christian
authors.initials: C
authors.lastname: Barillot