Accelerated and enhanced multiplicative deblurring schemes

Pierre-Alain Fayolle*, Alexander G. Belyaev

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We propose modifications of the Richardson–Lucy iterations (RL) and the Image Space Reconstruction Algorithm (ISRA) that demonstrate accelerated convergence and lead to improved image restoration results. We show that the iterations of RL, ISRA, and the proposed modifications can be interpreted as fixed-point iterations corresponding to the minimizers of certain variational problems. We demonstrate that combining each iteration of the proposed modifications with an adaptive image smoothing procedure leads to substantial improvements of the image restoration results. An implementation is available at https://github.com/fayolle/Mult_BBDeblur_demo.
Original languageEnglish
Article number109910
JournalSignal Processing
Volume232
Early online date3 Feb 2025
DOIs
Publication statusE-pub ahead of print - 3 Feb 2025

Keywords

  • Accelerated and enhanced RL and ISRA
  • Image deblurring
  • Variational image deconvolution

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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