JISE


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Journal of Information Science and Engineering, Vol. 34 No. 6, pp. 1441-1468


Meshfree Digital Total Variation Based Algorithm for Multiplicative Noise Removal


MUSHTAQ AHMAD KHAN, WEN CHEN+, ZHOUJIA FU+
AND ASMAT ULLAH
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering
College of Mechanics and Materials
Hohai University
Jiangsu, 210098 P.R. China
E-mail: {{
d2014017+; chenwen+; paul212063}@hhu.edu.cn; asmatullah75@gmail.com


The Digital Total Variation (DTV) filtering is a digitized energy method used to denoise the measured image data. Different from the traditional variation method, this technique applies to arbitrarily located data points and also has the built-in edge detective property. This paper introduces a novel meshfree algorithm (Kansa technique) using DTV method and Radial Basis Functions (RBFs) approximation for the numerical solution of the DTV-based model to remove the multiplicative noise from the measurements. This approach is structured on local collocations and multiquadric radial basis function. These features enable this method to eliminate noise from images while sharply resolving discontinuities. It is observed that the present methodology is fast, robust, and computationally efficient, requires simple post-processing, and can be easily implemented. The numerical experiments show that the proposed method performs well in visual improvement as well as peak signal-to-noise ratio compared with the recent total variation partial differential equation (PDE)-based methods for multiplicative noise removal.


Keywords: image denoising, digital total variation (DTV) filter, multiquadric radial basis function (MQ RBF), restoration equation, mesh method, meshfree method

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