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

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. (c) 2005 SPIE and IS&T.