Aliasing artefact index for image interpolation quality assessment

Olivier Rukundo, Samuel Schmidt

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

5 Citations (Scopus)
92 Downloads (Pure)

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.
Original languageEnglish
Title of host publicationOptoelectronic Imaging and Multimedia Technology V
PublisherSPIE - International Society for Optical Engineering
Publication date7 Nov 2018
Article number108171E
DOIs
Publication statusPublished - 7 Nov 2018
EventSPIE/COS Photonics Asia : Optoelectronic Imaging and Multimedia Technology V - Beijing International Convention Center, Beijing, China
Duration: 11 Oct 201813 Oct 2018
https://spie.org/PA/conferencedetails/optoelectronic-imaging-and-multimedia

Conference

ConferenceSPIE/COS Photonics Asia
LocationBeijing International Convention Center
CountryChina
CityBeijing
Period11/10/201813/10/2018
Internet address
SeriesProceedings of SPIE, the International Society for Optical Engineering
Volume10817
ISSN0277-786X

Fingerprint Dive into the research topics of 'Aliasing artefact index for image interpolation quality assessment'. Together they form a unique fingerprint.

Cite this