A nonconvex l1(l1 - l2) model for image restoration with impulse noise
A nonconvex l1(l1 - l2) model for image restoration with impulse noise
复制标题
用于脉冲噪声图像恢复的非凸 l(1)(l(1) - l(2)) 模型
DOI：
10.1016/j.cam.2020.112934
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发表时间：
2020-11-01
影响因子：
2.4
通讯作者：
Ni, Guoxi
中科院分区：
文献类型：
--
作者：
Liu, Jingjing;Ni, Anqi;Ni, Guoxi
在本文中，我们提出了一种具有模糊和脉冲噪声的图像恢复模型，它由数据拟合项和非凸正则化项组成，非凸正则化项是基于小波框架的l(1)-范数和l(2)-范数的加权差。组合模型很难用相应的欧拉拉格朗日方程来求解，这里我们用乘子交替方向法（ADMM）来求解。我们描述了算法的详细过程，并建立了算法的收敛性。不同模糊和不同脉冲噪声的实验结果表明，所提出的方法在标准信噪比（PSNR）、相对误差（ReErr）和视觉质量方面优于现有方法。 (C) 2020 Elsevier B.V. 保留所有权利。
In this paper, we propose a model for image restoration with blur and impulse noise, it is composed of data fitting term and a nonconvex regularization term, which is the weighted difference of l(1)-norm and l(2)-norm based on wavelet frame. The combined model is difficult to solve by the corresponding Euler Lagrangian equations, here we solve it by alternating direction method of multipliers (ADMM). We describe the detailed process of the algorithm, and establish the convergence of the algorithm. The experimental outcomes on different blurs and different impulse noises demonstrate that the proposed approach is better than those existing methods in terms of standard signal-to-noise ratio (PSNR), relative error (ReErr), and visual quality. (C) 2020 Elsevier B.V. All rights reserved.