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Multiquadric Radial Basis Function Approximation Scheme for Solution of Total Variation Based Multiplicative Noise Removal Model 被引量:1
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作者 Mushtaq Ahmad Khan Ahmed BAltamimi +4 位作者 Zawar Hussain Khan Khurram Shehzad Khattak Sahib Khan Asmat Ullah Murtaza Ali 《Computer Modeling in Engineering & Sciences》 SCIE EI 2021年第1期55-88,共34页
This article introduces a fastmeshless algorithm for the numerical solution nonlinear partial differential equations(PDE)by Radial Basis Functions(RBFs)approximation connected with the Total Variation(TV)-basedminimiz... This article introduces a fastmeshless algorithm for the numerical solution nonlinear partial differential equations(PDE)by Radial Basis Functions(RBFs)approximation connected with the Total Variation(TV)-basedminimization 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. 展开更多
关键词 Denoised image multiplicative and speckle noises total variation(TV)filter Euler-Lagrange restoration equation multiquadric radial basis functions meshless and mesh-based schemes
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