A new nonlocal variational bi-regularized image restoration model via split Bregman method

A new nonlocal variational bi-regularized image restoration model via split Bregman method
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一种新的基于分裂Bregman方法的非局部变分双正则化图像恢复模型

DOI:
10.1186/s13640-015-0072-7
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发表时间:
2015-06
影响因子:
2.4
通讯作者:
房胜
房胜
中科院分区:
计算机科学4区
文献类型:
--
作者:
Dong-Huan Jiang;Xue Tan;Yongquan Liang;房胜

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在本文中,我们提出了一个新的变分模型的图像恢复,将一个非局部电视正则化和非局部拉普拉斯正则化的图像。这两个正则化项利用了图像中的补丁对之间的非局部比较。新模型可以看作是CEP-L2模型的非局部版本。随后,提出了一种交替方向极小化和分裂Bregman迭代相结合的算法来求解新模型。数值实验结果表明,该方法比CEP-L2模型具有更好的图像恢复性能,特别是对低噪声图像。
In this paper, we propose a new variational model for image restoration by incorporating a nonlocal TV regularizer and a nonlocal Laplacian regularizer on the image. The two regularizing terms make use of nonlocal comparisons between pairs of patches in the image. The new model can be seen as a nonlocal version of the CEP-L2model. Subsequently, an algorithm combining the alternating directional minimization and the split Bregman iteration is presented to solve the new model. Numerical results verified that the proposed method has better performance for image restoration than CEP-L2model, especially for low noised images.
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影响因子: 1.3
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