Gibbs random field model based weight selection for the 2-D adaptive weighted median filter

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dc.citation.epage837en_US
dc.citation.issueNumber8en_US
dc.citation.spage831en_US
dc.citation.volumeNumber16en_US
dc.contributor.authorOnural, L.en_US
dc.contributor.authorAlp, M. B.en_US
dc.contributor.authorGürelli, M. I.en_US
dc.date.accessioned2015-07-28T12:07:10Z
dc.date.available2015-07-28T12:07:10Z
dc.date.issued1994en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractA generalized filtering method based on the minimization of the energy of the Gibbs model is described. The well-known linear and median filters are all special cases of this method. It is shown that, with the selection of appropriate energy functions, the method can be successfully used to adapt the weights of the adaptive weighted median filter to preserve different textures within the image while eliminating the noise. The newly developed adaptive weighted median filter is based on a 3 x 3 square neighborhood structure. The weights of the pixels are adapted according to the clique energies within this neighborhood structure. The assigned energies to 2- or 3-pixel cliques are based on the local statistics within a larger estimation window. It is shown that the proposed filter performance is better compared to some well-known similar filters like the standard, separable, weighted and some adaptive weighted median filters.en_US
dc.description.provenanceMade available in DSpace on 2015-07-28T12:07:10Z (GMT). No. of bitstreams: 1 10.1109-34.308480.pdf: 818903 bytes, checksum: 9641b419566fef1a6ecb9a9485dcdc4d (MD5)en
dc.identifier.doi10.1109/34.308480en_US
dc.identifier.issn0162-8828
dc.identifier.urihttp://hdl.handle.net/11693/13605
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/34.308480en_US
dc.source.titleIEEE Transactions on Pattern Analysis and Machine Intelligenceen_US
dc.subjectGihbs random field modelen_US
dc.subjectAdaptive filteringen_US
dc.subjectWeighted median filteren_US
dc.subjectImage noise filteringen_US
dc.titleGibbs random field model based weight selection for the 2-D adaptive weighted median filteren_US
dc.typeArticleen_US

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