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)


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
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


ConferenceSPIE/COS Photonics Asia
LocationBeijing International Convention Center
Internet address
SeriesProceedings of SPIE, the International Society for Optical Engineering

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

Cite this