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.