Fractional Conway Polynomials for Image Denoising with Regularized Fractional Power Parameters

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• 作者：Hamid A. Jalab ; Rabha W. Ibrahim
• 关键词：Fractional calculus ; Fractional differential operator ; Fractional integral operator ; Image denoising ; Conway polynomials ; 34SA08 ; 68U10 ; 94A08
• 刊名：Journal of Mathematical Imaging and Vision
• 出版年：2015
• 出版时间：March 2015
• 年：2015
• 卷：51
• 期：3
• 页码：442-450
• 全文大小：11,276 KB
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• 刊物类别：Computer Science
• 刊物主题：Computer Imaging, Vision, Pattern Recognition and Graphics
  Image Processing and Computer Vision
  Artificial Intelligence and Robotics
  Automation and Robotics
  
• 出版者：Springer Netherlands
• ISSN：1573-7683

文摘

Image denoising is a significant image processing problem that is difficult to study. The use of fractional masks based on fractional calculus (integral and differential)?operators has increased for image denoising. This paper proposes an image denoising algorithm that is based on the generalization of fractional Conway polynomials with regularized fractional power parameters. We operate the structures of fractional masks (differential and integral) by using \(n \times n\) processing masks on eight directions. The performance of the proposed algorithm is evaluated on the basis of visual perception and peak signal-to-noise ratio (PSNR). Theoretical analysis and experimental results demonstrate that the improvements achieved according to visual perception and PSNR values are comparable with Gaussian and Wiener filters.