A subband adaptive iterative shrinkage/thresholding algorithm

Ilker Bayram, Ivan W. Selesnick

Research output: Contribution to journalArticlepeer-review


We investigate a subband adaptive version of the popular iterative shrinkage/thresholding algorithm that takes different update steps and thresholds for each subband. In particular, we provide a condition that ensures convergence and discuss why making the algorithm subband adaptive accelerates the convergence. We also give an algorithm to select appropriate update steps and thresholds for when the distortion operator is linear and time invariant. The results in this paper may be regarded as extensions of the recent work by Vonesch and Unser.

Original languageEnglish (US)
Pages (from-to)1131-1143
Number of pages13
JournalIEEE Transactions on Signal Processing
Issue number3 PART 1
StatePublished - Mar 2010


  • Deconvolution
  • Fast algorithm
  • Shrinkage
  • Subband adaptive
  • Thresholding
  • Wavelet regularized inverse problem

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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