In this paper, a new relaxation model based on mean curvature for adaptive image restoration is proposed. To solve the problem efficiently, an alternating direction method of multipliers (ADMMs) is proposed. Furthermore, a rigorous convergence theory of the proposed algorithm is established. We also give the complexity analysis of our proposed method. Experimental results are provided to demonstrate the effectiveness and efficiency of the proposed method over a state-of-the-art method on synthetic and natural images.

中文翻译：

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通过平均曲率的松弛正则化进行自适应图像恢复

提出了一种基于平均曲率的松弛模型用于自适应图像复原。为了有效地解决该问题，提出了一种交替方向的乘法器（ADMM）方法。此外，建立了所提出算法的严格收敛理论。我们还对我们提出的方法进行了复杂性分析。实验结果证明了该方法在合成和自然图像上的有效性和效率。