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Image inpainting with adaptive linear predictor

  • Shanghai Jiao Tong University
  • SUNY Buffalo

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

1 Scopus citations

Abstract

In this paper, a novel examplar-based inpainting algorithm with adaptive linear predictor is proposed. The patches in the damaged region are sequentially estimated with a linear combination of several nearest neighboring patches. The number of candidate patch is automatically tuned to local contexts based on Bayesian Information Criterion (BIC). The flexibility of the order-adaptive predictor makes the proposed algorithm suitable for both structural regions and detailed textures. The multi-scale framework and a novel propagation order are also involved to further improve the inpainting performance. Compared to the state-of-the-art image inpainting algorithms, experimental results show that the proposed method gives comparative or better performance.

Original languageEnglish
Title of host publication2015 IEEE International Conference on Multimedia and Expo, ICME 2015
PublisherIEEE Computer Society
ISBN (Electronic)9781479970827
DOIs
StatePublished - Aug 4 2015
EventIEEE International Conference on Multimedia and Expo, ICME 2015 - Turin, Italy
Duration: Jun 29 2015Jul 3 2015

Publication series

NameProceedings - IEEE International Conference on Multimedia and Expo
Volume2015-August
ISSN (Print)1945-7871
ISSN (Electronic)1945-788X

Conference

ConferenceIEEE International Conference on Multimedia and Expo, ICME 2015
Country/TerritoryItaly
CityTurin
Period06/29/1507/3/15

Keywords

  • adaptive linear prediction
  • Bayesian Information Criterion
  • Image inpainting

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