Title :
Impulse noise removal by spectral clustering and regularization on graphs
Author :
Lezoray, Olivier ; Ta, Vinh Thong ; Elmoataz, Abderrahim
Author_Institution :
GREYC UMR CNRS 6072, Univ. de Caen Basse-Normandie, Caen
Abstract :
In this paper we present a method for impulse noise removal that makes use of spectral clustering and graph regularization. The image is modeled as a graph and local spectral analysis is performed to identify noisy and noise free pixels. On the set of noise free pixels, a topology adapted graph regularization is performed. Experimental results show the benefits of the proposed approach regarding the standard VMF when noise proportion is high.
Keywords :
graph theory; image denoising; impulse noise; pattern clustering; spectral analysis; image impulse noise removal; noise free pixel; spectral graph clustering; topology adapted graph regularization; Computational efficiency; Filtering; Filters; Graph theory; Image restoration; Image sensors; Noise reduction; Pixel; Spectral analysis; Topology;
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
DOI :
10.1109/ICPR.2008.4761401