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Image restoration with a high-order total variation minimization method

机译：用高阶总方差最小化方法进行图像复原

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摘要

In this paper, we propose a fast and efficient way to restore blurred and noisy images with a high-order total variation minimization technique. The proposed method is based on an alternating technique for image deblurring and denoising. It starts by finding an approximate image using a Tikhonov regularization method. This corresponds to a deblurring process with possible artifacts and noise remaining. In the denoising step, a high-order total variation algorithm is used to remove noise in the deblurred image. We see that the edges in the restored image can be preserved quite well and the staircase effect is reduced effectively in the proposed algorithm. We also discuss the convergence of the proposed regularization method. Some numerical results show that the proposed method gives restored images of higher quality than some existing total variation restoration methods such as the fast TV method and the modified TV method with the lagged diffusivity fixed-point iteration.
机译：在本文中，我们提出了一种快速有效的方法，可以使用高阶总方差最小化技术还原模糊和嘈杂的图像。所提出的方法基于用于图像去模糊和去噪的交替技术。首先使用Tikhonov正则化方法查找近似图像。这对应于具有可能的伪像和噪声残留的去模糊处理。在去噪步骤中，使用高阶总变化算法去除去模糊图像中的噪声。我们看到，在所提出的算法中，可以很好地保留还原图像中的边缘，并有效降低了阶梯效应。我们还将讨论所提出的正则化方法的收敛性。数值结果表明，与快速TV法，修正TV法等具有滞后扩散定点迭代的总TV恢复方法相比，所提方法具有更高的质量。

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  • 来源
    《Applied Mathematical Modelling》 |2013年第17期|8210-8224|共15页
  • 作者

    Xiao-Guang Lv; Yong-Zhong Song; Shun-Xu Wang; Jiang Le;

  • 作者单位

    School of Mathematical Sciences, Nanjing Normal University, Nanjing, Jiangsu 210097, PR China ,School of Science, Huaihai Institute of Technology, Lianyungang, Jiangsu 222005, PR China;

    School of Mathematical Sciences, Nanjing Normal University, Nanjing, Jiangsu 210097, PR China;

    School of Science, Huaihai Institute of Technology, Lianyungang, Jiangsu 222005, PR China;

    School of Science, Huaihai Institute of Technology, Lianyungang, Jiangsu 222005, PR China ,School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, PR China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Image restoration; Deblurring; Denoising; High-order; Regularization;

    机译：图像还原;去模糊;去噪;高阶正则化;

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