Parameter-free Plug-and-Play ADMM for image restoration
Parameter-free Plug-and-Play ADMM for image restoration
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DOI：
10.1109/icassp.2017.7952371
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发表时间：
2017-03
期刊：
影响因子：
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通讯作者：
Xiran Wang;Stanley H. Chan
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文献类型：
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作者：
Xiran Wang;Stanley H. Chan
即插即用 ADMM 是最近开发的经典 ADMM 算法的变体，它使用现成的图像降噪器替换其中一个子问题。尽管其明显是临时性质的，即插即用 ADMM 却产生了令人惊讶的良好图像恢复结果。然而，由于在即插即用 ADMM 中，降噪器被视为黑匣子，因此整个算法的行为在很大程度上是未知的。特别是，控制算法收敛速度的内部参数必须由用户调整，参数选择不当会导致结果严重恶化。在本文中，我们提出了一种无参数的即插即用 ADMM，其中内部参数作为优化的一部分进行更新。我们的算法源自广义近似消息传递，并进行了一些必要的修改。通过实验，我们发现新算法沿着可靠且快速的收敛路径产生解决方案。
Plug-and-Play ADMM is a recently developed variation of the classical ADMM algorithm that replaces one of the subproblems using an off-the-shelf image denoiser. Despite its apparently ad-hoc nature, Plug-and-Play ADMM produces surprisingly good image recovery results. However, since in Plug-and-Play ADMM the denoiser is treated as a black-box, behavior of the overall algorithm is largely unknown. In particular, the internal parameter that controls the rate of convergence of the algorithm has to be adjusted by the user, and a bad choice of the parameter can lead to severe degradation of the result. In this paper, we present a parameter-free Plug-and-Play ADMMwhere internal parameters are updated as part of the optimization. Our algorithm is derived from the generalized approximate message passing, with several essential modifications. Experimentally, we find that the new algorithm produces solutions along a reliable and fast converging path.