A novel time-frequency technique for multicomponent signal denoising

T. Oberlin, Sylvain Meignen, Stephen McLaughlin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)


Multicomponent signals, i.e. superpositions of modulated waves, arise in many physical or biological systems. Exploiting the particular structure of these signals, denoising methods based on time-frequency distributions often outperform standard techniques such as those based on diagonal estimation or sparsity approaches. Recently, a simple denoising technique based on local integration in scale of the wavelet transform was proposed. In spite of its behaviour being better compared to classical techniques for medium noise levels, it does not perform so well in other cases. We propose here a method to improve denoising behaviour based on a more accurate mode reconstruction technique. The method is detailed for time-frequency representation given by short-time Fourier and continuous wavelet transforms, with the emphasis placed on their differences.

Original languageEnglish
Title of host publication2013 Proceedings of the 21st European Signal Processing Conference (EUSIPCO)
ISBN (Print)9780992862602
Publication statusPublished - 2013
Event21st European Signal Processing Conference 2013 - Morocco, Marrakech, Morocco
Duration: 9 Sept 201313 Sept 2013


Conference21st European Signal Processing Conference 2013
Abbreviated titleEUSIPCO 2013


  • denoising
  • multicomponent signals
  • ridge
  • synchrosqueezing
  • Time-frequency

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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