On semismooth Newton's methods for total variation minimization

Kwok Po NG*, Liqun Qi, Yu Fei Yang, Yu Mei Huang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

69 Citations (Scopus)

Abstract

In [2], Chambolle proposed an algorithm for minimizing the total variation of an image. In this short note, based on the theory on semismooth operators, we study semismooth Newton's methods for total variation minimization. The convergence and numerical results are also presented to show the effectiveness of the proposed algorithms.

Original languageEnglish
Pages (from-to)265-276
Number of pages12
JournalJournal of Mathematical Imaging and Vision
Volume27
Issue number3
DOIs
Publication statusPublished - Apr 2007

Scopus Subject Areas

  • Statistics and Probability
  • Modelling and Simulation
  • Condensed Matter Physics
  • Computer Vision and Pattern Recognition
  • Geometry and Topology
  • Applied Mathematics

User-Defined Keywords

  • Denoising
  • Regularization
  • Semismooth Newton's methods
  • Total variation

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