A Novel Image Denoising Algorithm Based on Riemann-Liouville Definition

نویسندگان

  • Jinrong Hu
  • Yi-Fei Pu
  • Jiliu Zhou
چکیده

In this paper, a novel image denoising algorithm named fractional integral image denoising algorithm (FIIDA) is proposed, which based on fractional calculus Riemann-Liouville definition. The structures of n*n fractional integral masks of this algorithm on the directions of 135 degrees, 90 degrees, 45 degrees, 0 degrees, 180 degrees, 315 degrees, 270 degrees and 225 degrees are constructed and discussed. The denoising performance of FIIDA is measured using experiments according to subjective and objective standards of visual perception and PSNR values. The simulation results show that the FIIDA’s performance is prior to the Gaussian smoothing filter, especially when the noise standard deviation is less than 30.

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عنوان ژورنال:
  • JCP

دوره 6  شماره 

صفحات  -

تاریخ انتشار 2011