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Image Denoising Based on Adaptive Fractional Order Anisotropic Diffusion
  • KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Image Denoising Based on Adaptive Fractional Order Anisotropic Diffusion


Abstract

Recently, the method based on fractional order partial differential equation has been used in image processing. Usually, the optional order of fractional differentiation is determined by a lot of experiments. In this paper, a denoising model is proposed based on adaptive fractional order anisotropic diffusion. In the proposed model, the complexity of the local image texture is reflected by the local variance, and the order of the fractional differentiation is determined adaptively. In the process of the adaptive fractional order model, the discrete Fourier transform is applied to compute the fractional order difference as well as the dynamic evolution process. Experimental results show that the peak signal-to-noise ratio (PSNR) and structural similarity index measurement (SSIM) of the proposed image denoising algorithm is better than that of other some algorithms. The proposed algorithm not only can keep the detailed image information and edge information, but also obtain a good visual effect.


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Cite this article

[IEEE Style]
J. Yu, L. Tan, S. Zhou, L. Wang and C. Wang, "Image Denoising Based on Adaptive Fractional Order Anisotropic Diffusion," KSII Transactions on Internet and Information Systems, vol. 11, no. 1, pp. 436-450, 2017. DOI: 10.3837/tiis.2017.01.023.

[ACM Style]
Jimin Yu, Lijian Tan, Shangbo Zhou, Liping Wang, and Chaomei Wang. 2017. Image Denoising Based on Adaptive Fractional Order Anisotropic Diffusion. KSII Transactions on Internet and Information Systems, 11, 1, (2017), 436-450. DOI: 10.3837/tiis.2017.01.023.