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Comparison of the PDE-based regularization methods and a unifying framework

  • Bochao Su
  • , Xiaohua Zhang
  • , Wanyu Liu
  • , Li Li
  • Harbin Institute of Technology
  • Dalian University of Technology

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

Abstract

The frequent problems in computer vision consist of de-noising, artifact elimination as well as structure preserving or enhancing. PDE-based nonlinear diffusion filter may be one possibility to achieve those goals. In this paper, we perform comparison of three typical PDE-based regularization algorithms followed by the proposal of a general framework, which exploits fundamental significance for analyzing PDE-based regularization methods.

Original languageEnglish
Title of host publicationProceedings - 2014 4th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2014
EditorsJun-Bao Li
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages527-532
Number of pages6
ISBN (Electronic)9781479965755
DOIs
StatePublished - 22 Dec 2014
Event4th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2014 - Harbin, Heilongjiang, China
Duration: 18 Sep 201420 Sep 2014

Publication series

NameProceedings - 2014 4th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2014

Conference

Conference4th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2014
Country/TerritoryChina
CityHarbin, Heilongjiang
Period18/09/1420/09/14

Keywords

  • PDE
  • diffusion tensor
  • image processing
  • regularization

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