Title :
NL-Means and aggregation procedures
Author :
Salmon, J. ; Le Pennec, E.
Author_Institution :
Lab. de Probabilite et Modeles Aleatoires, Univ. Paris 7- Diderot, Chevaleret, France
Abstract :
Patch based denoising methods, such as the NL-Means, have emerged recently as simple and efficient denoising methods. This paper provides a new insight on those methods by showing their connection with recent statistical aggregation techniques. Within this aggregation framework, we propose some novel patch based denoising methods. We provide some theoretical justification and then explain how to implement them with a Monte Carlo based algorithm.
Keywords :
Monte Carlo methods; image denoising; statistical analysis; Monte Carlo based algorithm; NL-means procedures; aggregation procedures; patch based denoising; statistical aggregation techniques; Additive noise; Diffusion processes; Gaussian noise; Image processing; Kernel; Monte Carlo methods; Noise reduction; Pixel; Smoothing methods; Statistics; Diffusion processes; Gaussian noise; Image processing; Monte Carlo methods; Statistics;
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2009.5414512