Aliasing artefact index for image interpolation quality assessment

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

Abstract

A preliminary study of a non-reference aliasing artefact index (AAI) metric is presented in this paper. We focus on the effects of combining a full-reference metric and interpolation algorithm. The nearest neighbor algorithm (NN) is used as the gold standard against which test-algorithms are judged in terms of aliased structures. The structural similarity index (SSIM) metric is used to evaluate a test image (i.e. a test-algorithm's image) and a reference image (i.e. the NN's image). Preliminary experiments demonstrated promising effects of the AAI metric against state-of-the-art non-reference metrics mentioned. A new study may further develop the studied metric for potential applications in image quality adaptation and/or monitoring in medical imaging.

Details

Authors
External organisations
  • Aalborg University
Research areas and keywords

Keywords

  • Aliasing artefact index, Gold standard, Image interpolation, Nearest neighbor algorithm, Objective image quality metric, Structural similarity index, Test-algorithm
Original languageEnglish
Title of host publicationOptoelectronic Imaging and Multimedia Technology V
EditorsQionghai Dai, Tsutomu Shimura
PublisherSPIE
ISBN (Electronic)9781510622326
Publication statusPublished - 2018 Jan 1
Publication categoryResearch
Peer-reviewedYes
Externally publishedYes
EventOptoelectronic Imaging and Multimedia Technology V 2018 - Beijing, China
Duration: 2018 Oct 112018 Oct 12

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10817
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceOptoelectronic Imaging and Multimedia Technology V 2018
CountryChina
CityBeijing
Period2018/10/112018/10/12