Self-similarity based image super-resolution on frequency domain

Sae Jin Park, Oh Young Lee, Jong Ok Kim

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

10 Citations (Scopus)

Abstract

Self-similarity has been popularly exploited for image super resolution in recent years. Image is decomposed into LF (low frequency) and HF (high frequency) components, and similar patches are searched in the LF domain across the pyramid scales of the original image. Once a similar LF patch is found, the LF is combined with the corresponding HR patch, and we reconstruct the HR (high resolution) version. In this paper, we separately search similar LR and HR patches in the LF and HF domains, respectively. In addition, self-similarity based SR is applied to the new structure-texture domain instead of the existing LF and HF. Experimental results show that the proposed method outperforms several conventional SR algorithms based on self-similarity.

Original languageEnglish
Title of host publication2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013
DOIs
Publication statusPublished - 2013
Event2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013 - Kaohsiung, Taiwan, Province of China
Duration: 2013 Oct 292013 Nov 1

Publication series

Name2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013

Other

Other2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013
Country/TerritoryTaiwan, Province of China
CityKaohsiung
Period13/10/2913/11/1

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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