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dc.contributor.authorLee, Yuan-Kang
dc.contributor.authorDing, Jian-Jiun
dc.contributor.editorSkala, Václav
dc.date.accessioned2024-08-01T18:10:30Z-
dc.date.available2024-08-01T18:10:30Z-
dc.date.issued2024
dc.identifier.citationWSCG 2024: full papers proceedings: 32. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision, p. 371-376.en
dc.identifier.issn2464–4625 (online)
dc.identifier.issn2464–4617 (print)
dc.identifier.urihttp://hdl.handle.net/11025/57411
dc.format6 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencyen
dc.rights© Václav Skala - UNION Agencyen
dc.subjectostrost obrazucs
dc.subjectrozmazání obrazucs
dc.subjectbez odkazucs
dc.subjectoddělená vlnková transformacecs
dc.subjectdetekce hranycs
dc.subjecthodnocení kvality obrazucs
dc.titleSharpness Measurement by Edge-related Frequency Componentsen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedIn this paper, a novel no-reference image quality metric of sharpness is proposed. Our image quality metric is evaluated on two key attributes discerned during the assessment of image sharpness by the human visual system (HVS): 1. Image sharpness is principally contingent upon the salience of edges within the image. 2. With an increase in the decomposition level of the Discrete Wavelet Transform (DWT), the high-frequency coefficients correspond to higher spatial frequency information in an image. Experimental results show that in comparison to other state-of-the-art metrics, our method not only accurately assesses image sharpness in both defocus and motion blur scenarios but also showcases superior precision and broader applicability.en
dc.subject.translatedimage sharpnessen
dc.subject.translatedimage bluren
dc.subject.translatedno-referenceen
dc.subject.translateddiscrete wavelet transformen
dc.subject.translatededge detectionen
dc.subject.translatedimage quality assessmenten
dc.identifier.doihttps://doi.org/10.24132/10.24132/CSRN.3401.40
dc.type.statusPeer revieweden
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