An improved prediction of DCT-based image filters efficiency using regression analysis

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dc.contributor.authorRubel, Oleksii S.
dc.contributor.authorLukin, Volodymyr V.
dc.date.accessioned2015-01-14T10:13:18Z
dc.date.available2015-01-14T10:13:18Z
dc.date.issued2014en
dc.description.abstractenEfficiency of DCT-based filters for a wide-class of images is investigated. The study is carried out for additive white Gaussian noise (AWGN) case with several intensity levels. Local DCT-based filter is used as basic denoising technique. Nonlocal BM3D filter known as the state-of-the-art technique for AWGN removal is also exploited. A precise prediction method of denoising efficiency for several quality metrics is proposed. It is shown that statistics of DCT coefficients provides useful information. Regression models for analyzed filters and metrics are presented. The obtained dependence approximations of quality metrics on DCT statistics have high goodness of fit. One-parameter and multi-parameter fitting cases are considered. The most valuable DCT statistics are found.uk
dc.format.pagerangePp. 30-41uk
dc.identifier.citationRubel O. S. An improved prediction of DCT-based image filters efficiency using regression analysis / Oleksii S. Rubel, Volodymyr V. Lukin // Information and telecommunication sciences : international research journal. – 2014. – Vol. 5, N. 1(8). – Pp. 30–41. – Bibliogr.: 16 ref.uk
dc.identifier.urihttps://ela.kpi.ua/handle/123456789/10094
dc.language.isoenuk
dc.publisherNational Technical University of Ukraine “Kyiv Polytechnic Institute”uk
dc.publisher.placeKyiven
dc.sourceInformation and telecommunication sciences: international research journalen
dc.status.pubpublisheduk
dc.subject.udc681.3.21uk
dc.titleAn improved prediction of DCT-based image filters efficiency using regression analysisuk
dc.typeArticleen
thesis.degree.level-uk

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Information and telecommunication sciences: international research journal, Vol. 5, N. 1(8)