Image denoising with 2D scale-mixing complex wavelet transforms

Norbert Remenyi, Orietta Nicolis, Guy Nason, Brani Vidakovic

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)


This paper introduces an image denoising procedure based on a 2D scale-mixing complex-valued wavelet transform. Both the minimal (unitary) and redundant (maximum overlap) versions of the transform are used. The covariance structure of white noise in wavelet domain is established. Estimation is performed via empirical Bayesian techniques, including versions that preserve the phase of the complex-valued wavelet coefficients and those that do not. The new procedure exhibits excellent quantitative and visual performance, which is demonstrated by simulation on standard test images.

Original languageEnglish
Article number6918447
Pages (from-to)5165-5174
Number of pages10
JournalIEEE Transactions on Image Processing
Issue number12
Publication statusPublished - 1 Dec 2014


  • bivariate normal distribution
  • complex-valued wavelets
  • empirical bayes estimation
  • Image denoising
  • posterior mean
  • scale-mixing wavelet transform

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design


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