Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/102801
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dc.contributor.authorPavlyuk, E.en
dc.date.accessioned2021-08-31T15:05:25Z-
dc.date.available2021-08-31T15:05:25Z-
dc.date.issued2014-
dc.identifier.citationPavlyuk E. Stability of some segmentation methods based on markov random fields for analysis of aero and space images / E. Pavlyuk. — DOI 10.12988/ams.2014.311642 // Applied Mathematical Sciences. — 2014. — Vol. 8. — Iss. 5-8. — P. 391-396.en
dc.identifier.issn1312885X-
dc.identifier.otherFinal2
dc.identifier.otherAll Open Access, Green3
dc.identifier.otherhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84892995111&doi=10.12988%2fams.2014.311642&partnerID=40&md5=86e23638ab59f4ef5f73d24f17c6b9b0
dc.identifier.urihttp://hdl.handle.net/10995/102801-
dc.description.abstractThe paper is devoted to the stability of image segmentation methods based on Markov random fields for analysis of aero and space image with a Gaussian noise and blur. Segmentation problem is formulated in terms of finding a Bayes labeling of an Markov random field with maximum of a posteriori probability by the method of "simulated annealing". We study stability of variants of the algorithm using the Metropolis and Gibbs sampling, the system of neighborhoods with 8 and 24 neighbors and various coefficients of temperature reduction. © 2014 Evgeny Pavlyuk.en
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.sourceAppl. Math. Sci.2
dc.sourceApplied Mathematical Sciencesen
dc.subjectGAUSSIAN NOISEen
dc.subjectIMAGE SEGMENTATIONen
dc.subjectMARKOV RANDOM FIELDSen
dc.subjectSTABILITYen
dc.titleStability of some segmentation methods based on markov random fields for analysis of aero and space imagesen
dc.typeArticleen
dc.typeinfo:eu-repo/semantics/articleen
dc.typeinfo:eu-repo/semantics/publishedVersionen
dc.identifier.doi10.12988/ams.2014.311642-
dc.identifier.scopus84892995111-
local.contributor.employeePavlyuk, E., Ural Federal University, Office 613, Turgeneva str. 4, Ekaterinburg, 620075, Russian Federation
local.description.firstpage391-
local.description.lastpage396-
local.issue5-8-
local.volume8-
local.contributor.departmentUral Federal University, Office 613, Turgeneva str. 4, Ekaterinburg, 620075, Russian Federation
local.identifier.pure387657-
local.identifier.puredd613e09-8cdb-4eab-b1db-d79bbfb9f06buuid
local.identifier.eid2-s2.0-84892995111-
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