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

Thomas S. Denney Jr.; Stanley J. Reeves

doi:10.1117/1.2135747

1 October 2005 Bayesian image reconstruction from Fourier-domain samples using prior edge information

Thomas S. Denney Jr., Stanley J. Reeves

Author Affiliations +

Journal of Electronic Imaging, Vol. 14, Issue 4, 043009 (October 2005). https://doi.org/10.1117/1.2135747

Abstract

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.

©(2005) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Thomas S. Denney Jr. and Stanley J. Reeves "Bayesian image reconstruction from Fourier-domain samples using prior edge information," Journal of Electronic Imaging 14(4), 043009 (1 October 2005). https://doi.org/10.1117/1.2135747

Published: 1 October 2005

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