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An image denoising model based on a fourth-order nonlinear partial differential equation

机译:基于四阶非线性偏微分方程的图像去噪模型

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Image denoising is a challenging task in the fields of image processing and computer vision. Inspired by the good performance of nonlinear fourth-order models in recovering smooth region, we proposed a fourth-order image denoising model. Using the fixed point theorem, we established the existence and uniqueness of the entropy solution. Based on the fast explicit diffusion scheme (FED), numerical experiments illustrate the effectiveness of the suggested method in image denoising. The results have been compared with three famous fourth-order models, You and Kaveh (YK) model, Lysaker, Lundervold and Tai (LLT) model and the more recent mean curvature (MC) model. The proposed model has the superiority in terms of removing noise while preserving image features. (C) 2018 Elsevier Ltd. All rights reserved.
机译:在图像处理和计算机视觉领域,图像去噪是一项艰巨的任务。受到非线性四阶模型在恢复平滑区域中的良好性能的启发,我们提出了一种四阶图像去噪模型。使用不动点定理,我们确定了熵解的存在性和唯一性。基于快速显式扩散方案(FED),数值实验说明了该方法在图像去噪中的有效性。将结果与三个著名的四阶模型(You和Kaveh(YK)模型,Lysaker,Lundervold和Tai(LLT)模型以及最新的平均曲率(MC)模型进行了比较。提出的模型在去除噪声的同时保留图像特征方面具有优势。 (C)2018 Elsevier Ltd.保留所有权利。

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