Deep Learning for Image Denoising: A Survey

Chunwei Tian, Yong Xu*, Lunke Fei, Ke Yan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

57 Citations (Scopus)

Abstract

Since the proposal of big data analysis and Graphic Processing Unit (GPU), the deep learning technique has received a great deal of attention and has been widely applied in the field of imaging processing. In this paper, we have an aim to completely review and summarize the deep learning technologies for image denoising in recent years. Moreover, we systematically analyze the conventional machine learning methods for image denoising. Finally, we point out some research directions for the deep learning technologies in image denoising.

Original languageEnglish
Title of host publicationGenetic and Evolutionary Computing - Proceedings of the 12th International Conference on Genetic and Evolutionary Computing, 2018
EditorsBixia Sui, Jerry Chun-Wei Lin, Shih-Pang Tseng, Jeng-Shyang Pan
PublisherSpringer Verlag
Pages563-572
Number of pages10
ISBN (Print)9789811358401
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event12th International Conference on Genetic and Evolutionary Computing, ICGEC 2018 - Changzhou, China
Duration: 14 Dec 201817 Dec 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume834
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference12th International Conference on Genetic and Evolutionary Computing, ICGEC 2018
Country/TerritoryChina
CityChangzhou
Period14/12/1817/12/18

Keywords

  • Convolutional neural networks
  • Deep learning
  • GPU
  • Image denoising

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