Super-resolution algorithm using noise level adaptive dictionary

Shin Cheol Jeong, Yeong Wook Kang, Byung Cheol Song

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

3 Scopus citations

Abstract

this paper presents a noise-robust super-resolution algorithm. In learning phase, a dictionary classified according to noise level is constructed, and then a high-resolution image is synthesized using the dictionary in the inference phase. Experimental results show that the proposed algorithm outperforms the existing algorithms even for noisy images.

Original languageEnglish
Title of host publicationISCE 2010 - 14th IEEE International Symposium on Consumer Electronics
DOIs
StatePublished - 2010
Event14th IEEE International Symposium on Consumer Electronics, ISCE 2010 - Braunschweig, Germany
Duration: 7 Jun 201010 Jun 2010

Publication series

NameProceedings of the International Symposium on Consumer Electronics, ISCE

Conference

Conference14th IEEE International Symposium on Consumer Electronics, ISCE 2010
Country/TerritoryGermany
CityBraunschweig
Period7/06/1010/06/10

Keywords

  • Dictionary
  • Learning-based super-resolution
  • Noise

Fingerprint

Dive into the research topics of 'Super-resolution algorithm using noise level adaptive dictionary'. Together they form a unique fingerprint.

Cite this