High frequency super-resolution for image enhancement

Oh Young Lee, Sae Jin Park, Jae Woo Kim, Jong Ok Kim

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

Abstract

Bayesian based MF-SR (multi-frame superresolution) has been used as a popular and effective SR model. However, texture region is not reconstructed sufficiently because it works on the spatial domain. In this paper, we extend the MF-SR method to operate on the frequency domain for the improvement of HF information as much as possible. For this, we propose a spatially weighted bilateral total variation model as a regularization term for Bayesian estimation. Experimental results show that the proposed method can recover texture region with reduced noise, compared to conventional methods.

Original languageEnglish
Title of host publicationISCE 2014 - 18th IEEE International Symposium on Consumer Electronics
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479945924
DOIs
Publication statusPublished - 2014
Event18th IEEE International Symposium on Consumer Electronics, ISCE 2014 - Jeju, Korea, Republic of
Duration: 2014 Jun 222014 Jun 25

Publication series

NameProceedings of the International Symposium on Consumer Electronics, ISCE

Other

Other18th IEEE International Symposium on Consumer Electronics, ISCE 2014
CountryKorea, Republic of
CityJeju
Period14/6/2214/6/25

Keywords

  • high frequency SR
  • image enhancement
  • multi-frame SR
  • spatially weighted bilateral total variance

ASJC Scopus subject areas

  • Engineering(all)

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