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Bayesian image reconstruction from Fourier-domain samples using prior edge information

[+] Author Affiliations
Thomas S. Denney

Auburn University, Electrical and Computer Engineering, 200 Broun Hall, Auburn, Alabama 36849

Stanley J. Reeves

Auburn University, Electrical and Computer Engineering, 200 Broun Hall, Auburn, Alabama 36849

J. Electron. Imaging. 14(4), 043009 (December 06, 2005). doi:10.1117/1.2135747
History: Received October 25, 2004; Revised April 04, 2005; Accepted April 12, 2005; Published December 06, 2005; Online December 06, 2005
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We propose the Bayesian image reconstruction with prior edges (BIRPE) algorithm for reconstructing an image from Fourier-domain samples with prior edge information from a higher resolution image. A major difference between BIRPE and previous methods is that all edges are detected automatically, and no segmentation of the prior image is required. Also, an edge found in the prior image does not need to be confirmed by the observations; smoothing is reduced across the edge if either the prior image or the observations suggest an edge. Simulations and results on magnetic resonance spectroscopic data are presented that demonstrate the effectiveness of the BIRPE method.

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Citation

Thomas S. Denney, Jr. and Stanley J. Reeves
"Bayesian image reconstruction from Fourier-domain samples using prior edge information", J. Electron. Imaging. 14(4), 043009 (December 06, 2005). ; http://dx.doi.org/10.1117/1.2135747


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