Model-based Inverse Halftoning with Wavelet-Vaguelette Deconvolution

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dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameIEEE International Conference on Image Processingen_US
dc.citation.firstpage973
dc.citation.lastpage976
dc.citation.locationVancouver, Canadaen_US
dc.citation.volumeNumber3en_US
dc.contributor.authorNeelamani, Rameshen_US
dc.contributor.authorNowak, Robert Daviden_US
dc.contributor.authorBaraniuk, Richard G.en_US
dc.contributor.orgCenter for Multimedia Communications (http://cmc.rice.edu/)en_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T00:55:28Z
dc.date.available2007-10-31T00:55:28Z
dc.date.issued2000-09-01en
dc.date.modified2006-06-21en_US
dc.date.note2001-09-02en_US
dc.date.submitted2000-09-01en_US
dc.descriptionConference Paperen_US
dc.description.abstractIn this paper, we demonstrate based on the linear model of Kite that inverse halftoning is equivalent to the well-studied problem of deconvolution in the presence of colored noise. We propose the use of the simple and elegant wavelet-vaguelette deconvolution (WVD) algorithm to perform the inverse halftoning. Unlike previous wavelet-based algorithms, our method is model-based; hence it is adapted to different error diffusion halftoning techniques. Our inverse halftoning algorithm consists of inverting the convolution operator followed by denoising in the wavelet domain. For signals in a Besov space, our algorithm possesses asymptotically (as the number of samples nears infinity near-optimal rates of error decay. Hence for images in a Besov space, it is impossible to improve significantly on the inverse halftoning performance of the WVD algorithm at high resolutions. Using simulations, we verify that our algorithm outperforms or matches the performances of the best published inverse halftoning techniques in the mean square error (MSE) sense and also provides excellent visual performance.en_US
dc.description.sponsorshipTexas Instrumentsen_US
dc.description.sponsorshipDefense Advanced Research Projects Agencyen_US
dc.description.sponsorshipNational Science Foundationen_US
dc.identifier.citationR. Neelamani, R. D. Nowak and R. G. Baraniuk, "Model-based Inverse Halftoning with Wavelet-Vaguelette Deconvolution," vol. 3, 2000.
dc.identifier.doihttp://dx.doi.org/10.1109/ICIP.2000.899620en_US
dc.identifier.urihttps://hdl.handle.net/1911/20140
dc.language.isoeng
dc.subjectKite*
dc.subjectinverse halftoning*
dc.subjectwavelet-vaguelette deconvolution (WVD)*
dc.subjectBesov*
dc.subjectmean square error (MSE)*
dc.subject.keywordKiteen_US
dc.subject.keywordinverse halftoningen_US
dc.subject.keywordwavelet-vaguelette deconvolution (WVD)en_US
dc.subject.keywordBesoven_US
dc.subject.keywordmean square error (MSE)en_US
dc.subject.otherImage Processing and Pattern analysisen_US
dc.subject.otherWavelet based Signal/Image Processingen_US
dc.subject.otherMultiscale Methodsen_US
dc.titleModel-based Inverse Halftoning with Wavelet-Vaguelette Deconvolutionen_US
dc.typeConference paper
dc.type.dcmiText
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