Please use this identifier to cite or link to this item: http://nopr.niscpr.res.in/handle/123456789/7040
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dc.contributor.authorPatil, Anil A-
dc.contributor.authorSinghai, Jyoti-
dc.date.accessioned2010-01-01T11:30:57Z-
dc.date.available2010-01-01T11:30:57Z-
dc.date.issued2010-01-
dc.identifier.issn0975-1084 (Online); 0022-4456 (Print)-
dc.identifier.urihttp://hdl.handle.net/123456789/7040-
dc.description34-38en_US
dc.description.abstractThis paper suggests a soft thresholding multiresolution technique based on local variance estimation for image denoising. This adaptive thresholding with local variance estimation effectively reduce image noise and preserves edges. In proposed algorithm, 2D fast discrete curvelet transform (2D FDCT) out performed wavelet based image denoising. PSNR using 2D FDCT is approximately doubled and it also preserves features at boundary of an image.en_US
dc.language.isoen_USen_US
dc.publisherCSIRen_US
dc.sourceJSIR Vol.69(01) [January 2010]en_US
dc.subjectCurvelet transformsen_US
dc.subjectImage denoisingen_US
dc.subjectLocal varianceen_US
dc.subjectSparse representationen_US
dc.titleImage denoising using curvelet transform: an approach for edge preservationen_US
dc.typeArticleen_US
Appears in Collections:JSIR Vol.69(01) [January 2010]

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