A total variation wavelet inpainting model with multilevel fitting parameters

Tony Chan*, Jianhong Shen, Hao Min Zhou

*Corresponding author for this work

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

7 Scopus citations

Abstract

In [14], we have proposed two total variation (TV) minimization wavelet models for the problem of filling in missing or damaged wavelet coefficients due to lossy image transmission or communication. The proposed models can have effective and automatic control over geometric features of the inpainted images including sharp edges, even in the presence of substantial loss of wavelet coefficients, including in the low frequencies. In this paper, we investigate a modification of the model for noisy images to further improve the recovery properties by using multi-level parameters in the fitting term. Some new numerical examples are also shown to illustrate the effectiveness of the recovery.

Original languageEnglish (US)
Title of host publicationAdvanced Signal Processing Algorithms, Architectures, and Implementations XVI
DOIs
StatePublished - Nov 9 2006
EventAdvanced Signal Processing Algorithms, Architectures, and Implementations XVI - San Diego, CA, United States
Duration: Aug 15 2006Aug 16 2006

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6313
ISSN (Print)0277-786X

Conference

ConferenceAdvanced Signal Processing Algorithms, Architectures, and Implementations XVI
CountryUnited States
CitySan Diego, CA
Period08/15/0608/16/06

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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