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Proceedings Paper

Bayesian signal reconstruction from Fourier transform magnitude and x-ray crystallography
Author(s): Peter C. Doerschuk
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Paper Abstract

A signal reconstruction problem motivated by x-ray crystallography is solved using a Bayesian statistical approach. A Markov random field is used to describe the a priori information concerning the 0 - 1 signal. The data are inaccurate measurements of the magnitudes of the Fourier coefficients of the signal. The solution exploits the parallel between Bayesian statistics and statistical mechanics and uses the spherical model and asymptotic small noise approximations.

Paper Details

Date Published: 1 October 1991
PDF: 10 pages
Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); doi: 10.1117/12.48367
Show Author Affiliations
Peter C. Doerschuk, Purdue Univ. (United States)


Published in SPIE Proceedings Vol. 1569:
Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision
Su-Shing Chen, Editor(s)

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