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


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
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


Other18th IEEE International Symposium on Consumer Electronics, ISCE 2014
Country/TerritoryKorea, Republic of


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

ASJC Scopus subject areas

  • General Engineering


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