A Review of Image Denoising With Deep Learning

被引：5

作者：

Yapici, Ahmet ^{[1
]}

Akcayol, M. Ali ^{[2
]}

机构：

[1] Turksat AS, Dept Informat, Ankara, Turkey

[2] Gazi Univ, Dept Comp Engn, Ankara, Turkey

来源：

2ND INTERNATIONAL INFORMATICS AND SOFTWARE ENGINEERING CONFERENCE (IISEC) | 2021年

关键词：

image denoising; image restoration; video denoising; deep learning-based noise reduction; SPARSE REPRESENTATION; FACE RECOGNITION; NOISE; ALGORITHM;

D O I：

10.1109/IISEC54230.2021.9672379

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Satellite images can be corrupted by noise during image capture, transfer or due to bad environmental conditions. In daily life and scientific searches, the need for more accurate images are increasing. However, images are distorted by noise, resulting in lower visual image quality. For this reason, noise removal studies are carried out on images to increase the quality. Until now, various methods have been proposed to decrease noise and each technique have different advantages. This paper, summarizes the studies in the field of noise reduction in video and images and compares the studies with each other.

引用

页数：6

共 59 条

[1] Establishing strong imputation performance of a denoising autoencoder in a wide range of missing data problems [J].