Double deconvolution using a neural network

Chong Sze TONG*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

The restoration of a blurred digital image usually requires accurate knowledge of the blurring process which, however, may not always be available. This paper describes a double iterative scheme for the simultaneous identification of the blurring and its removal by making use of the neural network paradigm and assumption of physical constraints on the blurring process.

Original languageEnglish
Title of host publicationISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages662-665
Number of pages4
ISBN (Electronic)078031865X, 9780780318656
DOIs
Publication statusPublished - 1994
Event1994 International Symposium on Speech, Image Processing and Neural Networks, ISSIPNN 1994 - Hong Kong, Hong Kong
Duration: 13 Apr 199416 Apr 1994

Publication series

NameISSIPNN 1994 - 1994 International Symposium on Speech, Image Processing and Neural Networks, Proceedings

Conference

Conference1994 International Symposium on Speech, Image Processing and Neural Networks, ISSIPNN 1994
Country/TerritoryHong Kong
CityHong Kong
Period13/04/9416/04/94

Scopus Subject Areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Linguistics and Language

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