Underlying elements of image quality assessment: : Preference and terminology for communicating image quality characteristics

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dc.contributor.author Virtanen, Toni
dc.contributor.author Nuutinen, Mikko
dc.contributor.author Häkkinen, Jukka
dc.date.accessioned 2021-10-07T10:17:02Z
dc.date.available 2021-10-07T10:17:02Z
dc.date.issued 2020-03-04
dc.identifier.citation Virtanen , T , Nuutinen , M & Häkkinen , J 2020 , ' Underlying elements of image quality assessment: Preference and terminology for communicating image quality characteristics ' , Psychology of Aesthetics, Creativity and the Arts . https://doi.org/10.1037/aca0000312
dc.identifier.other PURE: 133286304
dc.identifier.other PURE UUID: b63d1ba8-69ff-4aa7-a278-4f393e018be5
dc.identifier.other ORCID: /0000-0003-0215-2238/work/101134917
dc.identifier.other ORCID: /0000-0001-5191-2438/work/101135767
dc.identifier.other ORCID: /0000-0002-7429-3710/work/101136269
dc.identifier.uri http://hdl.handle.net/10138/335046
dc.description.abstract Image quality markedly affects the evaluation of images, and its control is crucial in studies using natural visual scenes as stimuli. Various image elements, such as sharpness or naturalness, can impact how observers view images and more directly how they evaluate their quality. To gain a better understanding of the types of interactions between these various elements, we conducted a study with a large set of images with multiple overlapping distortions, covering a wide range of quality variation. Observers assigned a quality rating on a 0-10 scale plus a verbal description of the images, explaining the elements on which their rating was based. Regression model predicting image quality ratings using 68 attributes uncovered the link between verbal descriptions and quality ratings and the importance of the image quality rating for each of the 68 image attributes. Brightness, naturalness, and good colors seem to be related to the highest image quality preference. However, the most important elements for predicting good image quality were related to image fidelity such as graininess and sharpness. This indicates that a certain level of image fidelity must be achieved before more subjective associations with, for instance, naturalness can emerge. Of the attributes, 72% had a negative impact on the preference judgment. This negative bias may be due to the fact that there are more ways that observers can perceive an image to fail than to excel when they are asked to evaluate image quality. fi
dc.description.abstract Image quality markedly affects the evaluation of images, and its control is crucial in studies using natural visual scenes as stimuli. Various image elements, such as sharpness or naturalness, can impact how observers view images and, more directly, how they evaluate their quality. To gain a better understanding of the types of interactions between these various elements, we conducted a study with a large set of images with multiple overlapping distortions, covering a wide range of quality variation. Observers assigned a quality rating of the images on a 0–10 scale and gave a verbal description explaining the elements on which their rating was based. A regression model predicting image quality ratings using 68 attributes uncovered the link between verbal descriptions and quality ratings and the importance of the image quality rating for each of the 68 image attributes. Brightness, naturalness, and good colors seem to be related to the highest image quality preference. However, the most important elements for predicting good image quality were related to image fidelity such as graininess and sharpness. This indicates that a certain level of image fidelity must be achieved before more subjective associations with, for instance, naturalness can emerge. Of the attributes, 72% had a negative impact on the preference judgment. This negative bias may be due to the fact that there are more ways that observers can perceive an image to fail than to excel when they are asked to evaluate image quality. en
dc.format.extent 13
dc.language.iso eng
dc.relation.ispartof Psychology of Aesthetics, Creativity and the Arts
dc.rights unspecified
dc.rights.uri info:eu-repo/semantics/openAccess
dc.subject 515 Psychology
dc.subject aesthetic preference
dc.subject image quality
dc.subject attribute
dc.subject mean opinion score
dc.subject mixed method
dc.title Underlying elements of image quality assessment: : Preference and terminology for communicating image quality characteristics en
dc.type Article
dc.contributor.organization Medicum
dc.contributor.organization Department of Psychology and Logopedics
dc.description.reviewstatus Peer reviewed
dc.relation.doi https://doi.org/10.1037/aca0000312
dc.relation.issn 1931-3896
dc.rights.accesslevel openAccess
dc.type.version acceptedVersion

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