A novel image denoising algorithm based on riemann-liouville definition

作者：Hu Jinrong^*; Pu Yifei; Zhou Jiliu

来源：Journal of Computers, 2011, 6(7): 1332-1338.

DOI：10.4304/jcp.6.7.1332-1338

• De-noising
• Fractional calculus
• Fractional integrals
• Gaussian smoothing filter
• Image de-noising
• Image denoising algorithm
• Objective standard
• Simulation result
• Standard deviation
• Visual perception

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.

• 出版日期2011
• 单位四川大学