3D Wavelet Sub-Bands Mixing for Image Denoising

Pierrick Coupé 1 Pierre Hellier 1 Sylvain Prima 1 Charles Kervrann 2, 3 Christian Barillot 1
1 VisAGeS - Vision, Action et Gestion d'informations en Santé
INSERM - Institut National de la Santé et de la Recherche Médicale : U746, Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
2 Unité MIAJ - INRA - Mathématiques et Informatique Appliquées
3 VISTA - Vision spatio-temporelle et active
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
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 Non Local (NL) Means filter with wavelet sub-bands mixing. The proposed wavelet sub-bands mixing is based on a multi-resolution 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 sub-bands mixing outperforms the classical implementation of the NL-means filter in terms of denoising quality and computation time. Comparison with well- established methods, such as non linear 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.
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Article dans une revue
International Journal of Biomedical Imaging, Hindawi Publishing Corporation, 2008, pp.590183. 〈10.1155/2008/590183〉
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Pierrick Coupé, Pierre Hellier, Sylvain Prima, Charles Kervrann, Christian Barillot. 3D Wavelet Sub-Bands Mixing for Image Denoising. International Journal of Biomedical Imaging, Hindawi Publishing Corporation, 2008, pp.590183. 〈10.1155/2008/590183〉. 〈inria-00332001〉

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