Extensions to Total Variation denoising

Peter Blomgren*, Tony Chan, Pep Mulet

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

31 Scopus citations

Abstract

The Total Variation denoising method, proposed by Rudin, Osher and Fatermi, 92, is a PDE-based algorithm for edge-preserving noise removal. The images resulting from its application are usually piecewise constant, possibly with a staircase effect at smooth transitions and may contain significantly less fine details than the original non-degraded image. In this paper we present some extensions to this technique that aim to improve the above drawbacks, through redefining the Total Variation functional or the noise constraints.

Original languageEnglish (US)
Pages (from-to)367-375
Number of pages9
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume3162
DOIs
StatePublished - Dec 1 1997
EventAdvanced Signal Processing: Algorithms, Architectures and Implementations VII - San Diego, CA, United States
Duration: Jul 28 1997Jul 30 1997

Keywords

  • Image restoration
  • Iterative methods
  • Local constraints
  • Newton's method
  • Total Variation

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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