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Rician Noise Removal via a Learned Dictionary

机译:通过学习词典消除Rician噪声

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摘要

This paper proposes a new effective model for denoising images with Rician noise. The sparse representations of images have been shown to be efficient approaches for image processing. Inspired by this, we learn a dictionary from the noisy image and then combine the MAP model with it for Rician noise removal. For solving the proposed model, the primal-dual algorithm is applied and its convergence is studied. The computational results show that the proposed method is promising in restoring images with Rician noise.
机译:提出了一种新的有效的带里斯噪声的图像去噪模型。图像的稀疏表示已被证明是图像处理的有效方法。受此启发,我们从嘈杂的图像中学习了一个字典,然后将MAP模型与其结合以消除Rician噪声。为了解决该模型,应用了原始对偶算法并研究了其收敛性。计算结果表明,该方法在恢复具有Rician噪声的图像方面具有广阔的前景。

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  • 来源
    《Mathematical Problems in Engineering》 |2019年第4期|8535206.1-8535206.13|共13页
  • 作者单位

    Shenzhen Univ, Coll Math & Stat, Shenzhen Key Lab Adv Learning & Applicat, Shenzhen 518060, Peoples R China;

    Shenzhen Univ, Coll Math & Stat, Shenzhen Key Lab Adv Learning & Applicat, Shenzhen 518060, Peoples R China;

    Syracuse Univ, Dept Math, Syracuse, NY 13244 USA;

    Univ Missouri, Dept Math & Comp Sci, St Louis, MO 63121 USA;

    Ocean Univ China, Sch Math Sci, Qingdao 266100, Peoples R China;

    Shenzhen Univ, Coll Math & Stat, Shenzhen Key Lab Adv Learning & Applicat, Shenzhen 518060, Peoples R China;

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