Estimation of unknown structure parameters from high-resolution (S)TEM images: What are the limits?

被引:43
作者
den Dekker, A. J. [1 ]
Gonnissen, J. [2 ]
De Backer, A. [2 ]
Sijbers, J. [3 ]
Van Aert, S. [2 ]
机构
[1] Delft Univ Technol, Delft Ctr Syst & Control, NL-2628 CD Delft, Netherlands
[2] Univ Antwerp, B-2020 Antwerp, Belgium
[3] Univ Antwerp, Vis Lab, B-2610 Antwerp, Belgium
关键词
High resolution transmission electron microscopy (HRTEM); Electron microscope design and characterization; Data processing/image processing; MAXIMUM-LIKELIHOOD-ESTIMATION; ELECTRON-MICROSCOPY IMAGES; EXPERIMENTAL-DESIGN; Z-CONTRAST; ATOMIC-SCALE; COHERENT; PRECISION; OPTIMIZE;
D O I
10.1016/j.ultramic.2013.05.017
中图分类号
TH742 [显微镜];
学科分类号
摘要
Statistical parameter estimation theory is proposed as a quantitative method to measure unknown structure parameters from electron microscopy images. Images are then purely considered as data planes from which structure parameters have to be determined as accurately and precisely as possible using a parametric statistical model of the observations. For this purpose, an efficient algorithm is proposed for the estimation of atomic column positions and intensities from high angle annular dark field (HAADF) scanning transmission electron microscopy (STEM) images. Furthermore, the so-called Cramer-Rao lower bound (CRLB) is reviewed to determine the limits to the precision with which continuous parameters such as atomic column positions and intensities can be estimated. Since this lower bound can only be derived for continuous parameters, alternative measures using the principles of detection theory are introduced for problems concerning the estimation of discrete parameters such as atomic numbers. An experimental case study is presented to show the practical use of these measures for the optimization of the experiment design if the purpose is to decide between the presence of specific atom types using STEM images. (C) 2013 Elsevier B.V. All rights reserved.
引用
收藏
页码:34 / 43
页数:10
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