Abstract

A signal-reconstruction problem motivated by x-ray crystallography is (approximately) solved with a Bayesian statistical approach. The signal is 0–1 and periodic, and substantial statistical a priori information is known, which is modeled with a Markov random field. The data are inaccurate magnitudes of the Fourier coefficients of the signal. The solution is explicit, and the computational burden is independent of the signal dimension. The spherical model and asymptotic small noise expansions are used.

© 1991 Optical Society of America

Adaptive Bayesian signal reconstruction with a priori model implementation and synthetic examples for x-ray crystallography

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