L 0-norm and total variation for wavelet inpainting

Andy C. Yau, Xue-Cheng TAI, Kwok Po NG

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

In this paper, we suggest an algorithm to recover an image whose wavelet coefficients are partially lost. We propose a wavelet inpainting model by using L 0-norm and the total variation (TV) minimization. Traditionally, L 0-norm is replaced by L 1-norm or L 2-norm due to numerical difficulties. We use an alternating minimization technique to overcome these difficulties. In order to improve the numerical efficiency, we also apply a graph cut algorithm to solve the subproblem related to TV minimization. Numerical results will be given to demonstrate our advantages of the proposed algorithm.

Original languageEnglish
Title of host publicationScale Space and Variational Methods in Computer Vision - Second International Conference, SSVM 2009, Proceedings
Pages539-551
Number of pages13
DOIs
Publication statusPublished - 2009
Event2nd International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2009 - Voss, Norway
Duration: 1 Jun 20095 Jun 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5567 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2009
Country/TerritoryNorway
CityVoss
Period1/06/095/06/09

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

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