Localizing periodicity in near-field images
Statistical Mechanics
2016-08-31 v1 Materials Science
Optics
Abstract
We show that Bayesian inference, like that used in statistical mechanics, can guide the systematic construction of Fourier dark-field methods for localizing periodicity in near-field (e.g. scanning-tunneling and electron-phase-contrast) images. For crystals in an aperiodic field, the Fourier coefficient Ze^{i phi} combines with a prior estimate for background amplitude B to predict background phase (beta) values distributed with a probability p(beta - phi | Z,phi,B) inversely proportional to the amplitude P of the signal of interest, when this latter is treated as an unknown translation scaled to B.
Keywords
Cite
@article{arxiv.cond-mat/9711309,
title = {Localizing periodicity in near-field images},
author = {P. Fraundorf},
journal= {arXiv preprint arXiv:cond-mat/9711309},
year = {2016}
}
Comments
5 pages (4 figs, 13 refs) RevTeX; apps http://newton.umsl.edu/stei_lab