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A Fast High-Order Total Variation Minimization Method for Multiplicative Noise Removal

机译：快速高阶总方差最小化的乘性噪声消除

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摘要

Multiplicative noise removal problem has received considerable attention in recent years. The total variation regularization method for the solution of the noise removal problem can preserve edges well but has the sometimes undesirable staircase effect. In this paper, we propose a fast high-order total variation minimization method to restore multiplicative noisy images. The proposed method is able to preserve edges and at the same time avoid the staircase effect in the smooth regions. An alternating minimization algorithm is employed to solve the proposed high-order total variation minimization problem. We discuss the convergence of the alternating minimization algorithm. Some numerical results show that the proposed method gives restored images of higher quality than some existing multiplicative noise removal methods.
机译：近年来，乘法噪声消除问题已引起广泛关注。用于解决噪声消除问题的总变化正则化方法可以很好地保留边缘，但有时具有不希望的阶梯效应。在本文中，我们提出了一种快速的高阶总方差最小化方法来还原乘法噪声图像。所提出的方法能够保留边缘并且同时避免在光滑区域中的阶梯效应。采用交替最小化算法来解决所提出的高阶总变化最小化问题。我们讨论了交替最小化算法的收敛性。一些数值结果表明，与某些现有的乘性噪声消除方法相比，该方法可提供更高质量的恢复图像。

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  • 来源
    《Mathematical Problems in Engineering》 |2013年第3期|834035.1-834035.13|共13页
  • 作者

    Xiao-Guang Lv; Jiang Le; Jin Huang; Liu Jun;

  • 作者单位

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

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

    School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China;

    School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China;

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