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Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/624
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dc.contributor.authorDagher, Issamen_US
dc.contributor.authorTaleb, Catherineen_US
dc.date.accessioned2020-12-23T08:33:48Z-
dc.date.available2020-12-23T08:33:48Z-
dc.date.issued2013-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/624-
dc.description.abstractImage denoising involves the manipulation of the image data to produce a visually high quality image. This paper improves the Wiener filter in the wavelet domain without the usual zero mean assumption. An improved LESE (local expected square error) formula is derived. For each wavelet block, the center coefficient is estimated by comparing the LESE given by the usual Wiener filter and the improved LESE. The minimum between them is chosen. The improved filter gave a higher PSNR for all the test images and all the noise variances that we have used.en_US
dc.format.extent4 p.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.subjectWiener filteren_US
dc.subjectImage denoisingen_US
dc.subjectWavelet transformen_US
dc.titleImproved wavelet wiener estimator in image denoisingen_US
dc.typeConference Paperen_US
dc.relation.conferenceInternational Conference on Advances in Computational Tools for Engineering Applications (ACTEA) (2nd : 12-15 Dec 2012 : Beirut, Lebanon)en_US
dc.contributor.affiliationDepartment of Computer Engineeringen_US
dc.description.startpage311en_US
dc.description.endpage314en_US
dc.date.catalogued2018-02-19-
dc.description.statusPublisheden_US
dc.identifier.ezproxyURLhttp://ezsecureaccess.balamand.edu.lb/login?url=http://ieeexplore.ieee.org/document/6462891/en_US
dc.identifier.OlibID177890-
dc.relation.ispartoftext2012 2nd International Conference on Advances in Computational Tools for Engineering Applications (ACTEA)en_US
dc.provenance.recordsourceOliben_US
crisitem.author.parentorgFaculty of Engineering-
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