3D Wavelet Subbands Mixing for Image Denoising
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 m...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2008-01-01
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| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2008/590183 |
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| Summary: | 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. |
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| ISSN: | 1687-4188 1687-4196 |