3D Wavelet Subbands Mixing for Image Denoising

Abstract EN

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.