MULTI-ALGORITHM IMAGE DENOISING

Georgiana-Rodica Chelu (), Marius-Adrian Ghidel (), Denisa-Gabriela Olteanu (), Costin-Anton Boiangiu () and Ion Bucur ()
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Georgiana-Rodica Chelu: Politehnica University of Bucharest, Bucharest, Romania
Marius-Adrian Ghidel: Politehnica University of Bucharest, Bucharest, Romania
Denisa-Gabriela Olteanu: Politehnica University of Bucharest, Bucharest, Romania
Costin-Anton Boiangiu: Politehnica University of Bucharest, Bucharest, Romania
Ion Bucur: Politehnica University of Bucharest, Bucharest, Romania

Journal of Information Systems & Operations Management, 2018, vol. 12, issue 2, 411-421

Abstract: In spite of the thorough research that has been done in the field of image denoising, a generic algorithm able to preserve the details of an image at an acceptable level has not been yet discovered. Most methods account for a specific class of noise and provide suitable results only if the implicitly-determined control parameters of the image correspond to the method’s assumptions. Furthermore, many such methods reside on the presumption that noise is spatially-invariant and do not treat the other case. The purpose of this paper is to analyze the classical methods used in image denoising, to observe their limitations in order to decide how mixing different algorithms might correct their undesired behaviors and to set the scene for a new method appropriate for image denoising that would yield better results on a more varied set of images.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:rau:jisomg:v:12:y:2018:i:2:p:411-421

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