SIAM Journal on Imaging Sciences, Volume 14, Issue 2, Page 749-777, January 2021.
In this paper, we consider minimizing the $L_1/L_2$ term on the gradient for a limited-angle scanning problem in computed tomography (CT) reconstruction. We design a specific splitting framework for an unconstrained optimization model so that the alternating direction method of multipliers (ADMM) has guaranteed convergence under certain conditions. In addition, we incorporate a box constraint that is reasonable for imaging applications, and the convergence for the additional box constraint can also be established. Numerical results on both synthetic and experimental datasets demonstrate the effectiveness and efficiency of our proposed approach, showing significant improvements over the state-of-the-art methods in the limited-angle CT reconstruction.

中文翻译：

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通过 $L_1/L_2$ 最小化的有限角度 CT 重建

SIAM 成像科学杂志，第 14 卷，第 2 期，第 749-777 页，2021 年 1 月。
在本文中，我们考虑在计算机断层扫描 (CT) 重建中的有限角度扫描问题的梯度上最小化 $L_1/L_2$ 项。我们为无约束优化模型设计了一个特定的分裂框架，以便乘法器的交替方向法（ADMM）保证在某些条件下收敛。此外，我们引入了一个对成像应用合理的框约束，并且还可以建立附加框约束的收敛性。合成数据集和实验数据集的数值结果证明了我们提出的方法的有效性和效率，显示出在有限角度 CT 重建中比最先进的方法有显着改进。