3D Wavelet Subbands Mixing for Image Denoising

• Main Authors: Pierrick Coupé, Pierre Hellier, Sylvain Prima, Charles Kervrann, Christian Barillot
• Format: Article
• Language: English
• Published: Hindawi Limited 2008-01-01
• Series: International Journal of Biomedical Imaging
• Online Access: http://dx.doi.org/10.1155/2008/590183

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.