A Wavelet-Based Statistical Model for Image Restoration

dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameIEEE International Conference on Image Processingen_US
dc.citation.locationThessaloniki, Greeceen_US
dc.contributor.authorWan, Yien_US
dc.contributor.authorNowak, Robert Daviden_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T01:09:26Z
dc.date.available2007-10-31T01:09:26Z
dc.date.issued2001-10-20en
dc.date.modified2001-10-07en_US
dc.date.note2001-10-07en_US
dc.date.submitted2001-10-20en_US
dc.descriptionConference Paperen_US
dc.description.abstractIn this paper we develop a wavelet-based statistical method for solving the image restoration problem. In this approach, a signal prior is set up by modeling the image wavelet coefficients as independent Gaussian mixture random variables. We first specify a uniform (non-informative) distribution on the mixing parameters, which leads to a simple and efficient iterative algorithm for MAP estimation. This algorithm is similar to the EM algorithm in that it alternates between a state estimation step and a maximization step. Moreover, we show that our algroithm converges monotonically to a local maximum of the posterior distribution. We next generalize the result to non-uniform priors and develop an efficient integer programming algorithm that enables a similar alternating optimization procedure.en_US
dc.identifier.citationY. Wan and R. D. Nowak, "A Wavelet-Based Statistical Model for Image Restoration," 2001.
dc.identifier.doihttp://dx.doi.org/10.1109/ICIP.2001.959087en_US
dc.identifier.urihttps://hdl.handle.net/1911/20440
dc.language.isoeng
dc.subjectwavelet*
dc.subjectimage restoration*
dc.subjectMAP*
dc.subjectGaussian mixture*
dc.subjectEM algorithm*
dc.subject.keywordwaveleten_US
dc.subject.keywordimage restorationen_US
dc.subject.keywordMAPen_US
dc.subject.keywordGaussian mixtureen_US
dc.subject.keywordEM algorithmen_US
dc.titleA Wavelet-Based Statistical Model for Image Restorationen_US
dc.typeConference paper
dc.type.dcmiText
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