@article{Arunchai2023, 
author = {Areerat Arunchai and Thidaporn Seangwattana and Kanokwan Sitthithakerngkiet and Kamonrat Sombut},
title = {Image restoration by using a modified proximal point algorithm},
year = {2023},
journal = {AIMS Mathematics},
volume = {8},
number = {4},
pages = {9557-9575},
keywords = {convex minimization, image restoration, optimization, proximal point algorithm, variational inclusion problem},
url = {https://www.sciopen.com/article/10.3934/math.2023482},
doi = {10.3934/math.2023482},
abstract = {In this paper, we establish a modified proximal point algorithm for solving the common problem between convex constrained minimization and modified variational inclusion problems. The proposed algorithm base on the proximal point algorithm in [19] and the method of Khuangsatung and Kangtunyakarn in [21] by using suitable conditions in Hilbert spaces. The proposed algorithm is not only presented in this article; however has also been demonstrated to generate a robust convergence theorem. The proposed algorithm could be used to solve image restoration problems where the images have suffered a variety of blurring operations. Additionally, we contrast the signal-to-noise ratio (SNR) of the proposed algorithm against that of Khuangsatung and Kangtunyakarn's method in [21] in order to compare image quality.}
}