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Split Bregman Algorithm, Douglas-Rachford Splitting and Frame Shrinkage

机译:Split Bregman算法,Douglas-Rachford分裂和帧收缩

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We examine relations between popular variational methods in image processing and classical operator splitting methods in convex analysis. We focus on a gradient descent reprojection algorithm for image denoising and the recently proposed Split Bregman and alternating Split Bregman methods. By identifying the latter with the so-called Douglas-Rachford splitting algorithm we can guarantee its convergence. We show that for a special setting based on Parseval frames the gradient descent reprojection and the alternating Split Bregman algorithm are equivalent and turn out to be a frame shrinkage method.
机译:我们研究了图像处理中流行的变分方法与凸分析中的经典算子分裂方法之间的关系。我们专注于用于图像降噪的梯度下降重投影算法以及最近提出的Split Bregman和交替Split Bregman方法。通过使用所谓的Douglas-Rachford分裂算法来识别后者,我们可以保证其收敛性。我们表明,对于基于Parseval帧的特殊设置,梯度下降重投影和交替的Split Bregman算法是等效的,并且证明是一种帧收缩方法。

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