Improved denoising with robust fitting in the wavelet transform domain

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

3 Citations (Scopus)

Abstract

In this paper we present a new method for thresholding the coefficients in the wavelet transform domain based on the robust local polynomial regression technique. It is proven that the robust locally-weighted smoother excellently removes the outliers or extreme values by performing iterative reweighting. The proposed method combines the main advantages of multiresolution analysis and robust fitting. Simulation results show efficient denoising at low resolution levels. Besides, it provides simultaneously high density impulse noise removal in contrast to other adaptive shrinkage procedures. Performance has been determined by using quantitative measures, such as signal to noise ratio and root mean square error.

Original languageEnglish
Title of host publicationTechnological Innovation for Cloud-Based Engineering Systems - 6th IFIPWG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2015, Proceedings
EditorsLuis M. Camarinha-Matos, Thais A. Baldissera, Giovanni Di Orio, Francisco Marques
PublisherSpringer New York LLC
Pages179-187
Number of pages9
ISBN (Electronic)9783319167657
DOIs
Publication statusPublished - Jan 1 2015
Event6th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2015 - Costa de Caparica, Portugal
Duration: Apr 13 2015Apr 15 2015

Publication series

NameIFIP Advances in Information and Communication Technology
Volume450
ISSN (Print)1868-4238

Other

Other6th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2015
CountryPortugal
CityCosta de Caparica
Period4/13/154/15/15

Keywords

  • Nonparametric regression
  • Robust fitting
  • Wavelet shrinkage

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management

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  • Cite this

    Dineva, A., Várkonyi-Kóczy, A. R., & Tar, J. K. (2015). Improved denoising with robust fitting in the wavelet transform domain. In L. M. Camarinha-Matos, T. A. Baldissera, G. Di Orio, & F. Marques (Eds.), Technological Innovation for Cloud-Based Engineering Systems - 6th IFIPWG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2015, Proceedings (pp. 179-187). (IFIP Advances in Information and Communication Technology; Vol. 450). Springer New York LLC. https://doi.org/10.1007/978-3-319-16766-4_19