A Barzilai-Borwein gradient projection method for sparse signal and blurred image restoration

被引：35

作者：

Abubakar, Auwal Bala ^{[1
,2
]}

Kumam, Poom ^{[1
,3
,4
]}

Mohammad, Hassan ^{[2
]}

Awwal, Aliyu Muhammed ^{[1
,5
]}

机构：

[1] King Mongkuts Univ Technol Thonburi KMUTT, Fac Sci, Dept Math, KMUTTFixed Point Res Lab,KMUTT Fixed Point Theory, 126 Pracha Uthit Rd, Bangkok 10140, Thailand

[2] Bayero Univ, Fac Phys Sci, Dept Math Sci, Kano, Nigeria

[3] King Mongkuts Univ Technol Thonburi KMUTT, Fac Sci, Ctr Excellence, Theoret & Computat Sci Ctr TaCS CoE, Sci Lab Bldg,126 Pracha Uthit Rd, Bangkok 10140, Thailand

[4] China Med Univ, China Med Univ Hosp, Dept Med Res, Taichung 40402, Taiwan

[5] Gombe State Univ, Fac Sci, Dept Math, Gombe, Nigeria

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2020年 / 357卷 / 11期

关键词：

THRESHOLDING ALGORITHM; EQUATIONS; RECONSTRUCTION; RECOVERY; DESCENT; SYSTEMS;

D O I：

10.1016/j.jfranklin.2020.04.022

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present a Barzilai-Borwein gradient method using the hyperplane projection technique of Solodov and Svaiter (1998) for solving the non-smooth nonlinear monotone equation arising from the reformula-tion of the l(1) -norm regularized problem. The proposed method is an extension of the modified method by Liu and Duan (J. Inequal. Appl. 2015(1), 8, 2015) for solving signal and image restoration problems. The method is derivative-free and its search direction satisfies the sufficient descent condition. Numerical experiments presented show that the proposed method can recover sparse signals in fewer iterations and less CPU time and can reconstruct blurred images with higher quality compared to similar methods in the literature. (C) 2020 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.

引用

页码：7266 / 7285

页数：20

共 40 条

[1] An Efficient Conjugate Gradient Method for Convex Constrained Monotone Nonlinear Equations with Applications [J].