Open AccessA fast explicit diffusion algorithm of fractional order anisotropic diffusion for image denoising
Author(s) -
Zhiguang Zhang,
Qiang Liu,
Tianling Gao
Publication year - 2021
Publication title -
inverse problems and imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.755
H-Index - 40
eISSN - 1930-8345
pISSN - 1930-8337
DOI - 10.3934/ipi.2021018
Subject(s) - algorithm , anisotropic diffusion , noise reduction , stability (learning theory) , computer science , diffusion , noise (video) , mathematics , image (mathematics) , artificial intelligence , physics , machine learning , thermodynamics
In this paper, we mainly show a novel fast fractional order anisotropic diffusion algorithm for noise removal based on the recent numerical scheme called the Fast Explicit Diffusion. To balance the efficiency and accuracy of the algorithm, the truncated matrix method is used to deal with the iterative matrix in the model and its error is also estimated. In particular, we obtain the stability condition of the iteration by the spectrum analysis method. Through implementing the fast explicit format iteration algorithm with periodic change of time step size, the efficiency of the algorithm is greatly improved. At last, we show some numerical results on denoising tasks. Many experimental results confirm that the algorithm can more quickly achieve satisfactory denoising results.