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Image denoising based on combined neural networks filter

  • Junhong Chen*
  • , Qinyu Zhang
  • *Corresponding author for this work
  • Harbin Institute of Technology Shenzhen

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

Abstract

In this paper, a new image restoration method based on combined neural networks filter is proposed. This combined neural networks filter is posed by a BPNN filter and an image data fusion system based on self-organizing mapping neural networks. And this approach can use the corrupted image itself as training data to avoid the problem of how to choose the training data, which is most of the other neural networks denoising methods have to face, by using the distributed character of WGN. Experiment results show that the proposed method can denoise the noises effectively.

Original languageEnglish
Title of host publicationProceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 International Conference on Information Engineering and Computer Science, ICIECS 2009 - Wuhan, China
Duration: 19 Dec 200920 Dec 2009

Publication series

NameProceedings - 2009 International Conference on Information Engineering and Computer Science, ICIECS 2009

Conference

Conference2009 International Conference on Information Engineering and Computer Science, ICIECS 2009
Country/TerritoryChina
CityWuhan
Period19/12/0920/12/09

Keywords

  • Image data fusion
  • Image denoising
  • Neural network

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