Отрывок: Iterative multi-quadratic procedure As described in the previoussection, we can find such a cut of the graph G that it gets resolved into two trees. Then, it will be possible to a...
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dc.contributor.authorThang, P.C.-
dc.contributor.authorKopylov, A.V.-
dc.date.accessioned2018-11-13 15:52:12-
dc.date.available2018-11-13 15:52:12-
dc.date.issued2018-
dc.identifierDspace\SGAU\20181111\72375ru
dc.identifier.citationThang PC, Kopylov AV. Tree-serial parametric dynamic programming with flexible prior model for image denoising. Computer Optics 2018; 42(5): 838-845. DOI: 10.18287/2412-6179-2018-42-5-838-845.ru
dc.identifier.urihttps://dx.doi.org/10.18287/2412-6179-2018-42-5-838-845-
dc.identifier.urihttp://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Treeserial-parametric-dynamic-programming-with-flexible-prior-model-for-image-denoising-72375-
dc.description.abstractWe consider here image denoising procedures, based on computationally effective tree-serial parametric dynamic programming procedures, different representations of an image lattice by the set of acyclic graphs and non-convex regularization of a new type which allows to flexibly set a priori preferences. Experimental results in image denoising, as well as comparison with related methods, are provided. A new extended version of multi quadratic dynamic programming procedures for image denoising, proposed here, shows an improved accuracy for images of a different type.ru
dc.language.isorusru
dc.publisherНовая техникаru
dc.relation.ispartofseries42;5-
dc.subjectImage denoisingru
dc.subjectDynamic programmingru
dc.subjectBayesian optimizationru
dc.subjectMarkov random fields (MRFs)ru
dc.subjectGauss-Seidel iteration methodru
dc.titleTree-serial parametric dynamic programming with flexible prior model for image denoisingru
dc.typeArticleru
dc.textpartIterative multi-quadratic procedure As described in the previoussection, we can find such a cut of the graph G that it gets resolved into two trees. Then, it will be possible to a...-
dc.classindex.scsti28.23.15-
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