Total variation wavelet thresholding

Tony F. Chan, Hao Min Zhou*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

We propose using Partial Differential Equation (PDE) techniques in wavelet based image processing to remove noise and reduce edge artifacts generated by wavelet thresholding. We employ a variational framework, in particular the minimization of total variation (TV), to select and modify the retained wavelet coefficients so that the reconstructed images have fewer oscillations near edges while noise is smoothed. Numerical experiments show that this approach improves the reconstructed image quality in wavelet compression and in denoising.

Original languageEnglish (US)
Pages (from-to)315-341
Number of pages27
JournalJournal of Scientific Computing
Volume32
Issue number2
DOIs
StatePublished - Aug 2007
Externally publishedYes

Bibliographical note

Funding Information:
Research supported in part by grants ONR-N00017-96-1-0277, NSF DMS-9973341 and DMS-0410062 and NIH contract P 20 MH65166.

Keywords

  • Image processing
  • Total variation minimization
  • Wavelet

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Numerical Analysis
  • General Engineering
  • Computational Theory and Mathematics
  • Computational Mathematics
  • Applied Mathematics

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