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

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 - 1 Apr 2007

Keywords

  • 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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