@Article{cmes.2021.011163,
AUTHOR = {Mushtaq Ahmad Khan, Ahmed B. Altamimi, Zawar Hussain Khan, Khurram Shehzad Khattak, Sahib Khan, Asmat Ullah, Murtaza Ali},
TITLE = {Multiquadric Radial Basis Function Approximation Scheme for Solution of Total Variation Based Multiplicative Noise Removal Model},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {126},
YEAR = {2021},
NUMBER = {1},
PAGES = {55--88},
URL = {http://www.techscience.com/CMES/v126n1/40866},
ISSN = {1526-1506},
ABSTRACT = {This article introduces a fast meshless algorithm for the numerical solution nonlinear partial differential equations
(PDE) by Radial Basis Functions (RBFs) approximation connected with the Total Variation (TV)-based minimization functional and to show its application to image denoising containing multiplicative noise. These capabilities
used within the proposed algorithm have not only the quality of image denoising, edge preservation but also the
property of minimization of staircase effect which results in blocky effects in the images. It is worth mentioning
that the recommended method can be easily employed for nonlinear problems due to the lack of dependence on a
mesh or integration procedure. The numerical investigations and corresponding examples prove the effectiveness
of the recommended algorithm regarding the robustness and visual improvement as well as peak-signal-to-noise
ratio (PSNR), signal-to-noise ratio (SNR), and structural similarity index (SSIM) corresponded to the current
conventional TV-based schemes.},
DOI = {10.32604/cmes.2021.011163}
}