Skip navigation
Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/54406
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGavrovska, A.-
dc.contributor.authorSamčović, A.-
dc.contributor.authorDujković, D.-
dc.coverage.spatialМинскen_US
dc.date.accessioned2024-02-27T09:45:16Z-
dc.date.available2024-02-27T09:45:16Z-
dc.date.issued2023-
dc.identifier.citationGavrovska, A. No-reference Perception Based Image Quality Evaluation Analysis using Approximate Entropy / A. Gavrovska, A. Samčović, D. Dujković // Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) : Proceedings of the 16th International Conference, October 17–19, 2023, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2023. – P. 283–286.en_US
dc.identifier.urihttps://libeldoc.bsuir.by/handle/123456789/54406-
dc.description.abstractDue to extensive relevance across many disciplines, interest of no-reference image quality evaluation has been increased. The main goal is to assess the visual quality of an image using an objective metric that should be highly consistent with the subjective scores given by viewers. Well- known naturalness and perception based metrics include patch level distortion estimation and may show specific effects when comparing to high difference mean opinion scores. In this paper such effects are demonstrated, as well the possibility of using approximate entropy to overcome such manifestations. The obtained results show that approximate entropy technique can be used as an estimator in order to additionally distinguish image information related to subjective index.en_US
dc.language.isoenen_US
dc.publisherBSUen_US
dc.subjectматериалы конференцийen_US
dc.subjectapproximate entropyen_US
dc.subjectperceptionen_US
dc.subjectdistortion typesen_US
dc.titleNo-reference Perception Based Image Quality Evaluation Analysis using Approximate Entropyen_US
dc.typeArticleen_US
Appears in Collections:Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023)

Files in This Item:
File Description SizeFormat 
Gavrovska_No_reference.pdf480.01 kBAdobe PDFView/Open
Show simple item record Google Scholar

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.