DocumentCode :
3495800
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
fYear :
2009
fDate :
7-10 Nov. 2009
Firstpage :
2977
Lastpage :
2980
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;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
ISSN :
1522-4880
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2009.5414512
Filename :
5414512
Link To Document :
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