A novel n-L1 image restoration approach

This article presents a variational image restoration model and an accelerated algorithm to recover a clear image from a noisy and blurred version. The model involves solving a high-order nonlinear partial differential equation, which can be computationally expensive. This paper proposes the use of the accelerated alternating direction method of multipliers (ADMM) to solve a constrained minimization problem. The method is based on a variable splitting scheme and an augmented Lagrangian method, resulting in a fast and convergent algorithm. The paper presents a convergence analysis of the proposed algorithm under certain conditions. Numerical results and comparisons demonstrate that our model and algorithm outperform some state-of-the-art algorithms for image restoration in terms of computational time.