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Please use this identifier to cite or link to this item: https://doi.org/10.1117/1.1426386
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dc.titleImage deconvolution using wavelet-based regularization
dc.contributor.authorShen, L.
dc.date.accessioned2014-10-28T02:36:43Z
dc.date.available2014-10-28T02:36:43Z
dc.date.issued2002-01
dc.identifier.citationShen, L. (2002-01). Image deconvolution using wavelet-based regularization. Journal of Electronic Imaging 11 (1) : 5-10. ScholarBank@NUS Repository. https://doi.org/10.1117/1.1426386
dc.identifier.issn10179909
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/103396
dc.description.abstractIn this paper, we propose a wavelet-based regularization algorithm for image deconvolution problems whose blurring filter is a low pass filter of an M-band wavelet. The perfect reconstruction formula of this M-band wavelet is used to establish our wavelet-based regularization algorithm. The simulations shew that our proposed algorithm for image deconvolution performs better than that of the Wiener filter and some other wavelet-based deconvolution algorithms in terms of the improvement in signal-to-noise ratio. © 2002 SPIE and IS&T.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1117/1.1426386
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentMATHEMATICS
dc.description.doi10.1117/1.1426386
dc.description.sourcetitleJournal of Electronic Imaging
dc.description.volume11
dc.description.issue1
dc.description.page5-10
dc.description.codenJEIME
dc.identifier.isiut000173757500001
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