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dc.contributor.authorWan, Yi
Nowak, Robert David
dc.creatorWan, Yi
Nowak, Robert David
dc.date.accessioned 2007-10-31T01:09:26Z
dc.date.available 2007-10-31T01:09:26Z
dc.date.issued 2001-10-20
dc.date.submitted 2001-10-20
dc.identifier.citation Y. Wan and R. D. Nowak, "A Wavelet-Based Statistical Model for Image Restoration," 2001.
dc.identifier.urihttps://hdl.handle.net/1911/20440
dc.description Conference Paper
dc.description.abstract In 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.
dc.language.iso eng
dc.subjectwavelet
image restoration
MAP
Gaussian mixture
EM algorithm
dc.title A Wavelet-Based Statistical Model for Image Restoration
dc.type Conference paper
dc.date.note 2001-10-07
dc.citation.bibtexName inproceedings
dc.date.modified 2001-10-07
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)
dc.subject.keywordwavelet
image restoration
MAP
Gaussian mixture
EM algorithm
dc.citation.location Thessaloniki, Greece
dc.citation.conferenceName IEEE International Conference on Image Processing
dc.type.dcmi Text
dc.type.dcmi Text
dc.identifier.doihttp://dx.doi.org/10.1109/ICIP.2001.959087


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  • DSP Publications [508]
    Publications by Rice Faculty and graduate students in digital signal processing.
  • ECE Publications [1289]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students

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