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Denoising Algorithm Based on Generalized Fractional Integral Operator with Two Parameters

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  • Hamid A. Jalab
  • Rabha W. Ibrahim

Abstract

In this paper, a novel digital image denoising algorithm called generalized fractional integral filter is introduced based on the generalized Srivastava-Owa fractional integral operator. The structures of fractional masks of this algorithm are constructed. The denoising performance is measured by employing experiments according to visual perception and PSNR values. The results demonstrate that apart from enhancing the quality of filtered image, the proposed algorithm also reserves the textures and edges present in the image. Experiments also prove that the improvements achieved are competent with the Gaussian smoothing filter.

Suggested Citation

  • Hamid A. Jalab & Rabha W. Ibrahim, 2012. "Denoising Algorithm Based on Generalized Fractional Integral Operator with Two Parameters," Discrete Dynamics in Nature and Society, Hindawi, vol. 2012, pages 1-14, May.
    • Handle: RePEc:hin:jnddns:529849
    DOI: 10.1155/2012/529849
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    Cited by:

    1. Ghanbari, Behzad & Atangana, Abdon, 2020. "A new application of fractional Atangana–Baleanu derivatives: Designing ABC-fractional masks in image processing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).

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