DocumentCode :
2465169
Title :
A weighted variational method for the removal of mixed noise
Author :
Barcelos, Celia A Z ; Barcelos, Emilio Z.
Author_Institution :
Fac. of Math., Fed. Univ. of Uberlandia, Uberlandia, Brazil
fYear :
2012
fDate :
14-17 Oct. 2012
Firstpage :
496
Lastpage :
501
Abstract :
In this paper the authors present a novel variational method for the reconstruction of images corrupted by non-uniformly distributed noise. The additive noise model has been studied extensively, using variational techniques such as the Rudin, Osher and Fatemi model. However, the reconstruction of images corrupted by non-Gaussian noise has not yet been thoroughly studied. The proposed model includes a balance between the data term and the regularization term in the energy functional, taking into account the statistical control of the parameters and the position of the noisy points related to the edges presented in the image. The parameters are determined by the given observed noisy image. The obtained results have shown the effectiveness and robustness in restoring images with multiplicative noise or mixed Gaussian noise, while preserving edges and small structures belonging to the image.
Keywords :
Gaussian noise; image denoising; image restoration; statistical analysis; variational techniques; Fatemi model; Osher model; Rudin model; additive noise model; data term; edge preservation; energy functional; image reconstruction; image restoration; mixed Gaussian noise; mixed noise removal; multiplicative noise; nonGaussian noise; nonuniformly distributed noise; regularization term; statistical parameter control; weighted variational method; Image edge detection; Image reconstruction; Mathematical model; Noise; Noise measurement; Noise reduction; Speckle; Image denoising; Impulsive noise; Mixed noise; Mixture of Gaussians; Variational pde model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4673-1713-9
Electronic_ISBN :
978-1-4673-1712-2
Type :
conf
DOI :
10.1109/ICSMC.2012.6377773
Filename :
6377773
Link To Document :
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