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dc.contributor.authorWan, Yi
Nowak, Robert David
dc.creatorWan, Yi
Nowak, Robert David
dc.date.accessioned 2007-10-31T01:09:13Z
dc.date.available 2007-10-31T01:09:13Z
dc.date.issued 1999-07-20
dc.date.submitted 1999-07-20
dc.identifier.citation Y. Wan and R. D. Nowak, "A Bayesian Multiscale Approach to Joint Image Restoration and Edge Detection," 1999.
dc.identifier.urihttps://hdl.handle.net/1911/20436
dc.description Conference paper
dc.description.abstract This paper presents a novel wavelet-based method for simultaneous image restoration and edge detection. The Bayesian framework developed here is general enough to treat a wide class of linear inverse problems involving (white or colored) Gaussian observation noises, but we focus on convolution operators. In our new approach, a signal prior is developed by modeling the signal/image wavelet coefficients as independent Gaussian mixture random variables. We specify a uniform (non-informative) distribution on the mixing parameters, which leads to an extremely simple iterative algorithm for joint MAP restoration and edge detection. This algorithm is similar to the popular EM algorithm in that it alternates between a state estimation step and a maximization step, yet it is much simpler in each step and has a very intuitive derivation. Moreover, we show that our algorithm converges monotonically to a local maximum of the posterior distribution. Experimental results show that this new method can perform better than wavelet-vaguelette type methods that are based on linear inverse filtering followed by wavelet coefficient denoising.
dc.language.iso eng
dc.subjectimage restoration
edge detection
Gaussian observation noises
joint MAP
EM algorithm
wavelet-vaguelette
dc.title A Bayesian Multiscale Approach to Joint Image Restoration and Edge Detection
dc.type Conference paper
dc.date.note 2001-09-02
dc.citation.bibtexName inproceedings
dc.date.modified 2001-09-02
dc.contributor.orgCenter for Multimedia Communications (http://cmc.rice.edu/)
dc.subject.keywordimage restoration
edge detection
Gaussian observation noises
joint MAP
EM algorithm
wavelet-vaguelette
dc.citation.location Denver, CO
dc.citation.conferenceName Wavelet Applications in Signal and Image Processing
dc.type.dcmi Text
dc.type.dcmi Text
dc.identifier.doihttp://dx.doi.org/10.1117/12.366822


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  • DSP Publications [508]
    Publications by Rice Faculty and graduate students in digital signal processing.
  • ECE Publications [1278]
    Publications by Rice University Electrical and Computer Engineering faculty and graduate students

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