Please use this identifier to cite or link to this item: http://hdl.handle.net/10995/102801
Title: Stability of some segmentation methods based on markov random fields for analysis of aero and space images
Authors: Pavlyuk, E.
Issue Date: 2014
Citation: Pavlyuk 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.
Abstract: The 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.
Keywords: GAUSSIAN NOISE
IMAGE SEGMENTATION
MARKOV RANDOM FIELDS
STABILITY
URI: http://hdl.handle.net/10995/102801
Access: info:eu-repo/semantics/openAccess
SCOPUS ID: 84892995111
PURE ID: 387657
dd613e09-8cdb-4eab-b1db-d79bbfb9f06b
ISSN: 1312885X
DOI: 10.12988/ams.2014.311642
Appears in Collections:Научные публикации, проиндексированные в SCOPUS и WoS CC

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