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Improved Denoising with Robust Fitting in the Wavelet Transform Domain

  • Adrienn DinevaEmail author
  • Annamária R. Várkonyi-Kóczy
  • József K. Tar
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 450)

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.

Keywords

Wavelet shrinkage Robust fitting Nonparametric regression 

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Copyright information

© IFIP International Federation for Information Processing 2015

Authors and Affiliations

  • Adrienn Dineva
    • 1
    Email author
  • Annamária R. Várkonyi-Kóczy
    • 2
  • József K. Tar
    • 3
  1. 1.Doctoral School of Applied Informatics and Applied Mathematics Óbuda UniversityBudapestHungary
  2. 2.Bánki Donát Faculty of Mechanical and Safety EngineeringInstitute of Mechatronics and Vehicle Engineering Óbuda UniversityBudapestHungary
  3. 3.John von Neumann Faculty of InformaticsÓbuda UniversityBudapestHungary

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