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首页> 外文期刊>Journal of visual communication & image representation >Split Bregmanized anisotropic total variation model for image deblurring
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Split Bregmanized anisotropic total variation model for image deblurring

机译:分裂Bregmanized各向异性总变异模型用于图像去模糊

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摘要

In this paper, an effective image deblurring model is proposed to preserve sharp image edges by suppressing the stair-casing arising in the total variation (TV) based method by using the anisotropic total variation. To solve the difficult L1 norm problems, the split Bregman iteration is employed. Several synthetic degraded images are used for experiments. Comparison results are also made with total variation and nonlocal total variation based method. Experimental results show that the proposed method not only is robust to noise and different blur kernels, but also performs well on blurring images with more detailed textures, and the stair-casing effect is well suppressed. (C) 2015 Elsevier Inc. All rights reserved.
机译:在本文中,提出了一种有效的图像去模糊模型,该方法通过使用各向异性总变化量来抑制基于总变化量(TV)的方法中产生的阶梯形空间,从而保留清晰的图像边缘。为了解决困难的L1范数问题,采用了分裂的Bregman迭代。几个合成的退化图像用于实验。还使用基于总变量和基于非局部总变量的方法进行比较。实验结果表明,该方法不仅对噪声和不同的模糊核具有鲁棒性,而且在纹理更细腻的图像模糊处理中表现良好,并且很好地抑制了楼梯框效应。 (C)2015 Elsevier Inc.保留所有权利。

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