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dc.contributor.authorWILSON, SIMON PAUL
dc.date.accessioned2009-09-18T16:20:54Z
dc.date.available2009-09-18T16:20:54Z
dc.date.issued2001
dc.date.submitted2001en
dc.identifier.citationWilson, S.P., Stefanou, G `Image segmentation using the double Markov random field, with application to land use estimation? in Proceedings of IEEE International Conference on Image Processing, 1, IEEE, 2001, pp 742-745en
dc.identifier.otherY
dc.identifier.otherYen
dc.identifier.urihttp://hdl.handle.net/2262/32970
dc.descriptionPUBLISHEDen
dc.description.abstractWe describe the double Markov random field, a natural hierarchical model for a Bayesian approach to model-based textured image segmentation. The model is difficult to implement, even using Markov chain Monte Carlo (MCMC) methods, so we describe an approximation that is computationally feasible. This is applied to a satellite image. We emphasise the valuable additional information about uncertainties in the segmentation that can be gained from the use of MCMC.en
dc.description.sponsorshipResearch made possible through Project MOUMIR, a 5th Framework funded Research Network.en
dc.format.extent742-745en
dc.format.extent475161 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherIEEEen
dc.relation.ispartofseries1en
dc.rightsYen
dc.subjectStatisticsen
dc.titleImage segmentation using the double Markov random field, with application to land use estimationen
dc.typeConference Paperen
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/swilson


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