On semismooth Newton's methods for total variation minimization

Michael K. Ng, Liqun Qi, Yu Fei Yang, Yu Mei Huang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

71 Citations (Scopus)


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
Issue number3
Publication statusPublished - 1 Apr 2007


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

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Software
  • Applied Mathematics
  • Computer Vision and Pattern Recognition


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