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Multi-Algorithm Image Denoising

Author

Listed:
  • 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)

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.

Suggested Citation

  • Georgiana-Rodica Chelu & Marius-Adrian Ghidel & Denisa-Gabriela Olteanu & Costin-Anton Boiangiu & Ion Bucur, 2018. "Multi-Algorithm Image Denoising," Journal of Information Systems & Operations Management, Romanian-American University, vol. 12(2), pages 411-421, December.
    • Handle: RePEc:rau:jisomg:v:12:y:2018:i:2:p:411-421
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    File URL: http://www.rebe.rau.ro/RePEc/rau/jisomg/Wi18/JISOM-WI18-A17.pdf
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