Communications in Information and Systems

Volume 20 (2020)

Number 4

A review of image denoising methods

Pages: 461 – 480

DOI: https://dx.doi.org/10.4310/CIS.2020.v20.n4.a4

Authors

Hua Wang (School of Information and Electrical Engineering, Ludong University, Yantai, China)

Linwei Fan (School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, China)

Qiang Guo (School of Computer Science and Technology, Shandong University of Finance and Economics, Jinan, China)

Caiming Zhang (School of Software, Shandong University, Jinan, China)

Abstract

Image denoising is a fundamental and important task in the field of digital image processing and computer vision. Image noise concatenation inevitably occurs during image acquisition and transmission, which leads to the degradation of image quality. The presence of noise has some negative effects on various practical applications such as object recognition, medical image analysis, and hyperspectral remote sensing. A lot of research work has provided a solution to this problem, and many methods have been developed in the literature. This paper focuses on classifying some representative works in the field of image denoising, and provides a brief review with several promising directions for further investigation in the future.

Full Text (PDF format)

This work was in part supported by the National Natural Science Foundation of China under Grant 61873145, in part by the NSFC Joint Fund with Zhejiang under Grant U1609218, in part by the Natural Science Foundation of Shandong Province under Grant ZR2018BF009 and Grant ZR2017JL029, and in part by the Science and Technology Innovation Program for Distinguished Young Talents of Shandong Province Higher Education Institutions under Grant 2019KJN045.

Received 7 August 2020

Published 2 December 2020