A primal-dual method for the Meyer model of cartoon and texture decomposition

You Wei Wen*, Hai Wei Sun, Kwok Po NG

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

8 Citations (Scopus)


In this paper, we study the original Meyer model of cartoon and texture decomposition in image processing. The model, which is a minimization problem, contains an l1-based TV-norm and an l-based G-norm. The main idea of this paper is to use the dual formulation to represent both TV-norm and G-norm. The resulting minimization problem of the Meyer model can be given as a minimax problem. A first-order primal-dual algorithm can be developed to compute the saddle point of the minimax problem. The convergence of the proposed algorithm is theoretically shown. Numerical results are presented to show that the original Meyer model can decompose better cartoon and texture components than the other testing methods.

Original languageEnglish
Article numbere2224
JournalNumerical Linear Algebra with Applications
Issue number2
Publication statusPublished - Mar 2019

Scopus Subject Areas

  • Algebra and Number Theory
  • Applied Mathematics

User-Defined Keywords

  • G-norm
  • image decomposition
  • Meyer's model
  • primal-dual algorithm
  • total variation


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