Kernel-based fourth-order diffusion for image noise removal |
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Authors: | Yu-Qian Yang Cheng-Yi Zhang |
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Affiliation: | 1. School of Mathematics and Statistics, Xidian University, Xi'an, Shaanxi 710075, China;2. Department of Mathematics and Mechanics of School of Science, Xi'an Polytechnic University, Xi'an, Shaanxi 710048, China |
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Abstract: | The fourth-order partial differential equations have good performance on noise smoothing and edge preservation without creating blocky effects on smooth regions. However, for low signal-to-noise ratio images, the discrimination between edges and noise is a challenging problem. A novel kernel-based fourth-order diffusion is proposed in this paper. It introduces a kernelized gradient operator in the fourth-order diffusion process, which leads to more effective noise removal capability. Experiment results show that this method outperforms several previous anisotropic diffusion methods for noise removal and edge preservation. |
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Keywords: | diffusion image filter Kernel method noise removal anisotropic |
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