DocumentCode :
236904
Title :
A new fractional-order variational model for speckled de-noising
Author :
Hacini, Meriem ; Hachouf, Fella ; Djemal, Khalifa
Author_Institution :
Lab. d´ Autom. et de Robot., Univ. Constantine, Constantine, Algeria
fYear :
2014
fDate :
10-12 Dec. 2014
Firstpage :
1
Lastpage :
6
Abstract :
In this paper, a novel speckled image de-noising algorithm is proposed. A fractional-order multiplicative variational model is included as a multiplicative constraint in the regularization problem thereby the appropriate regularization parameter will be controlled by the optimization process itself. An adaptive selection method based on image regions property is used for the selection of the appropriate fractional-order value. The proposed algorithm not only overcomes the disadvantage of generating artificial edges but also has the advantage of de-noising and edges preservation.Experimental results show that the fractional order multiplicative variational model can improve the Peak Signal to Noise Ratio (PSNR) of image, preserve image structures and overcomes the disadvantage of generating artificial edges in the de-noising process.
Keywords :
image denoising; optimisation; speckle; variational techniques; PSNR; adaptive selection method; artificial edge generation; edge preservation; fractional-order multiplicative variational model; optimization process; peak signal to noise ratio; speckled image denoising algorithm; Image denoising; Image edge detection; Mathematical model; Noise reduction; PSNR; Speckle; Fractional- order; Image De-noising; Multiplicative Variational model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Visual Information Processing (EUVIP), 2014 5th European Workshop on
Conference_Location :
Paris
Type :
conf
DOI :
10.1109/EUVIP.2014.7018384
Filename :
7018384
Link To Document :
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