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A relaxed Newton-Picard like method for Huber variant of total variation based image restoration

机译:一种类似牛顿-皮卡德的轻松方法,用于基于总变异的Huber变异图像恢复

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摘要

In this paper, we propose an effective iteration method for Huber variant of total variation based image restoration by exploiting the structure of the problem. We call the proposed method relaxed Newton-Picard like method. This method is easy to implement and cost-effective. We prove the convergence of the method by using the theory on semismooth functions. Experimental results show that the proposed method is more efficient than the alternating minimization method based on multiplicative half-quadratic reformulation and is competitive with the state of the art alternating direction method of multipliers. (C) 2019 Elsevier Ltd. All rights reserved.
机译:在本文中,我们通过利用问题的结构,提出了一种有效的迭代方法,用于基于全变化的图像恢复的Huber变体。我们将所提出的方法称为类似牛顿-皮卡德的宽松方法。该方法易于实施且具有成本效益。我们利用半光滑函数理论证明了该方法的收敛性。实验结果表明,所提出的方法比基于乘法半二次重构的交替最小化方法更有效,并且与现有的乘法器交替方向方法相竞争。 (C)2019 Elsevier Ltd.保留所有权利。

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