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A Novel Image Denoising Algorithm Based on Riemann-Liouville Definition

Author(s): Jinrong HU | Yifei Pu | Jiliu Zhou

Journal: Journal of Computers
ISSN 1796-203X

Volume: 6;
Issue: 7;
Start page: 1332;
Date: 2011;
Original page

Keywords: fractional calculus | fractional integral | fractional integral mask | image denoising | Gaussian smoothing filter

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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