A survey on image processing in noisy environment by fuzzy logic, image fusion, neural network, and non-local means

Kun Yu Tien, Hooman Samani, Jui Hua Lui

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

As time goes by, our technology gets improve day by day. We can know that it gets better in robotic technology. Robots try to social with human beings immediately. For the input, image processing becomes more important because it can make sure the human's actions and reactions. It is unavoidable that get some noise when the camera takes photo as input. Thus, noise removal is a key technology for image processing. We choose four kinds of noise removal's methods to introduce. There are fuzzy logical, image fusion, artificial neural network, non-local means. We find papers which were published during 2015 to 2017 and introduce what's different between them and traditional method. At the end of this paper, we use PSNR as the compared standard to check their advantages and disadvantages.

Original languageEnglish
Title of host publication2017 International Automatic Control Conference, CACS 2017
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-6
Number of pages6
ISBN (Electronic)9781538639009
DOIs
Publication statusPublished - 7 Feb 2018
Event2017 International Automatic Control Conference, CACS 2017 - Pingtung, Taiwan, Province of China
Duration: 12 Nov 201715 Nov 2017

Publication series

Name2017 International Automatic Control Conference, CACS 2017
Volume2017-November

Conference

Conference2017 International Automatic Control Conference, CACS 2017
Country/TerritoryTaiwan, Province of China
CityPingtung
Period12/11/1715/11/17

Keywords

  • fuzzy logic
  • image fusion
  • neural network
  • noise removal
  • non-local means

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