New hybrid variational recovery model for blurred images with multiplicative noise

Yiqiu Dong, Tieyong ZENG*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

A new hybrid variational model for recovering blurred images in the presence of multiplicative noise is proposed. Inspired by previous work on multiplicative noise removal, an I-divergence technique is used to build a strictly convex model under a condition that ensures the uniqueness of the solution and the stability of the algorithm. A split-Bregman algorithm is adopted to solve the constrained minimisation problem in the new hybrid model efficiently. Numerical tests for simultaneous deblurring and denoising of the images subject to multiplicative noise are then reported. Comparison with other methods clearly demonstrates the good performance of our new approach.

Original languageEnglish
Pages (from-to)263-282
Number of pages20
JournalEast Asian Journal on Applied Mathematics
Volume3
Issue number4
DOIs
Publication statusPublished - Nov 2013

Scopus Subject Areas

  • Applied Mathematics

User-Defined Keywords

  • Bregman algorithm
  • Convex model
  • Image deblurring
  • Multiplicative noise
  • Split
  • Total variation
  • Variational model

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