A hybrid Markov random field model for bilevel cutset reconstruction

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We propose a hybrid Markov random field (MRF) model and a two stage cutset-MRF approach for reconstructing bilevel images from cutsets. We show that the proposed approach leads to substantial improvements over previous cutset-MRF approaches in terms of both reconstruction error and visual quality (continuity of reconstructed segments and preservation of image structure). The proposed approach approaches the performance of pattern-based approaches without the additional memory requirements and training overhead. We also show that it outperforms inpainting approaches adapted to bilevel cutset reconstruction.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Pages3523-3527
Number of pages5
ISBN (Electronic)9781467399616
DOIs
StatePublished - Aug 3 2016
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: Sep 25 2016Sep 28 2016

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2016-August
ISSN (Print)1522-4880

Other

Other23rd IEEE International Conference on Image Processing, ICIP 2016
CountryUnited States
CityPhoenix
Period9/25/169/28/16

Keywords

  • Inpainting
  • MRF
  • Unsupervised

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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