AN ALTERNATING DIRECTION METHOD OF MULTIPLIERS WITH THE CONDITIONAL GRADIENT TOTAL VARIATION METHOD FOR LINEAR INVERSE PROBLEMS

A. Bentbib, A. Bouhamidi, K. Kreit
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Abstract

Abstract In this paper, we study the ill-posed problem using total variation regularization. To solve such a problem, we use an alternating direction method of multipliers to split our problem into two sub-problems. The novelty of our paper is in the use of the conditional gradient total variation method (CGTV) we have recently introduced. The second split- ting sub-problem is solved by transforming the obtained optimization problem to a general Sylvester matrix equation and then an orthogonal projection method is used to solve the obtained matrix equation. We give proof of the convergence of this method. Some numerical examples and applications to image restoration are given to illustrate the effectiveness of the proposed method.
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线性反问题的乘子交替方向法与条件梯度全变分法
摘要本文用全变分正则化方法研究了一类病态问题。为了解决这样的问题,我们使用乘法器的交替方向方法将问题分成两个子问题。本文的新颖之处在于使用了我们最近介绍的条件梯度总变分法(CGTV)。将得到的优化问题转化为一般的Sylvester矩阵方程,然后用正交投影法对得到的矩阵方程进行求解。给出了该方法的收敛性证明。通过数值算例和在图像恢复中的应用,说明了该方法的有效性。
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