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A variational model based on split Bregman method for multiplicative noise removal

机译:基于分裂Bregman方法的乘积噪声去除模型

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摘要

It is well known that total variation (TV) regularizer leads to the staircase effect, the higher order variational methods give rise to the restored image blurred. In this paper, we propose a novel variational model for multiplicative noise removal. The proposed model can automatically adjust the first and second order regularization terms. To solve such an objective function effectively, the split Bregman and primal-dual methods are employed in our numerical algorithm. Our experimental results show that the proposed method is more effective to filter out the multiplicative noise compared with the recent methods. (C) 2015 Elsevier GmbH. All rights reserved.
机译:众所周知,总变化量(TV)调节器会导致阶梯效应,高阶变化量方法会导致恢复的图像模糊。在本文中,我们提出了一种用于乘性噪声消除的新颖变分模型。提出的模型可以自动调整一阶和二阶正则化项。为了有效地解决此类目标函数,在我们的数值算法中采用了分裂Bregman方法和原始对偶方法。我们的实验结果表明,与最近的方法相比,该方法可以更有效地滤除乘法噪声。 (C)2015 Elsevier GmbH。版权所有。

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