An iterative super resolution algorithm based on adaptive FIR Wiener filtering

Kyle Xiang Zhang, Yuk Hee Chan, Wan Chi Siu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Aiming at image/video super resolution applications, this paper presents a spatially adaptive FIR wiener filter for super resolution reconstruction. Missing high resolution samples can be estimated as the weighted sum of nearby low resolution samples. In the proposed algorithm, the optimal weighting coefficients for each of nearby low resolution samples are determined with a distance-based correlation model of samples and iteratively refined according to the most updated estimates of the missing high resolution samples. Both objective and subjective measurements in our simulations show that the proposed algorithm can produce a better result as compared with some conventional algorithms across different noise conditions.
Original languageEnglish
Title of host publicationAPSIPA ASC 2010 - Asia-Pacific Signal and Information Processing Association Annual Summit and Conference
Pages125-128
Number of pages4
Publication statusPublished - 1 Dec 2010
Event2nd Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2010 - Biopolis, Singapore
Duration: 14 Dec 201017 Dec 2010

Conference

Conference2nd Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2010
Country/TerritorySingapore
CityBiopolis
Period14/12/1017/12/10

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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