Image Denoising Based on Adaptive Fractional Order Anisotropic Diffusion

• Jimin Yu,
• Lijian Tan,
• Shangbo Zhou,
• Liping Wang,
• Chaomei Wang,

Vol. 11, No. 1, January 29, 2017
10.3837/tiis.2017.01.023, Download Paper (Free):

• Fractional order partial differential equation
• image processing
• fractional differentiation
• anisotropic diffusion
• image texture
• local variance

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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