An Optimized Blockwise Non Local Means Denoising Filter for 3D Magnetic Resonance Images
Centre National de la Recherche Scientifique · Inserm · +2 more institutions
Abstract
A critical issue in image restoration is the problem of noise removal while keeping the integrity of relevant image information. Denoising is a crucial step to increase image quality and to improve the performance of all the tasks needed for quantitative imaging analysis. The method proposed in this paper is based on a 3-D optimized blockwise version of the nonlocal (NL)-means filter (Buades, , 2005). The NL-means filter uses the redundancy of information in the image under study to remove the noise. The performance of the NL-means filter has been already demonstrated for 2-D images, but reducing the computational burden is a critical aspect to extend the method to 3-D images. To overcome this problem, we…
Citation impact
- FWCI
- 22.70
- Percentile
- 100%
- References
- 64
Authors
3- CBChristian BarillotCorresponding
Centre National de la Recherche Scientifique, Inserm, Institut de Recherche en Informatique et Systèmes Aléatoires, Université de Rennes
- HIHal Id Inserm
Centre National de la Recherche Scientifique, Inserm, Institut de Recherche en Informatique et Systèmes Aléatoires, Université de Rennes
- CBChristian Barillot
Centre National de la Recherche Scientifique, Institut de Recherche en Informatique et Systèmes Aléatoires, Université de Rennes
Topics & keywords
- Filter (signal processing)
- Computer science
- Noise reduction
- Redundancy (engineering)
- Anisotropic diffusion
- Smoothing
- Computational complexity theory
- Algorithm