A fast algorithm for a mean curvature based image denoising model using augmented lagrangian method

Wei Zhu, Xue Cheng Tai*, Tony Chan

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Recently, many variational models using high order derivatives have been proposed to accomplish advanced tasks in image processing. Even though these models are effective in fulfilling those tasks, it is very challenging to minimize the associated high order functionals. In [33], we focused on a recently proposed mean curvature based image denoising model and developed an efficient algorithm to minimize it using augmented Lagrangian method, where minimizers of the original high order functional can be obtained by solving several low order functionals. Specifically, these low order functionals either have closed form solutions or can be solved using FFT. Since FFT yields exact solutions to the associated equations, in this work, we consider to use only approximations to replace these exact solutions in order to reduce the computational cost. We thus employ the Gauss-Seidel method to solve those equations and observe that the new strategy produces almost the same results as the previous one but needs less computational time, and the reduction of the computational time becomes salient for images of large sizes.

Original languageEnglish (US)
Title of host publicationEfficient Algorithms for Global Optimization Methods in Computer Vision - International Dagstuhl Seminar, Revised Selected Papers
PublisherSpringer Verlag
Pages104-118
Number of pages15
ISBN (Print)9783642547737
DOIs
StatePublished - Jan 1 2014
Event2011 International Dagstuhl Seminar 11471 on Efficient Algorithms for Global Optimization Methods in Computer Vision - Dagstuhl Castle, Germany
Duration: Nov 20 2011Nov 25 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8293 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2011 International Dagstuhl Seminar 11471 on Efficient Algorithms for Global Optimization Methods in Computer Vision
CountryGermany
CityDagstuhl Castle
Period11/20/1111/25/11

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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