Bayesian signal reconstruction from Fourier transform magnitude and x-ray crystallography

Peter C. Doerschuk

doi:10.1117/12.48367

1 October 1991 Bayesian signal reconstruction from Fourier transform magnitude and x-ray crystallography

Peter C. Doerschuk

Proceedings Volume 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision; (1991) https://doi.org/10.1117/12.48367
Event: San Diego, '91, 1991, San Diego, CA, United States

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.

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Peter C. Doerschuk "Bayesian signal reconstruction from Fourier transform magnitude and x-ray crystallography", Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); https://doi.org/10.1117/12.48367

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