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Title
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Statistical parameter estimation theory : principles and simulation studies
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Author
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Abstract
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| In this chapter, the principles of statistical parameter estimation theory for a quantitative analysis of atomic-resolution electron microscopy images are introduced. Within this framework, electron microscopy images are described by a parametric statistical model. Here, parametric models are introduced for different types of electron microscopy images: reconstructed exit waves, annular dark-field (ADF) scanning transmission electron microscopy (STEM) images, and simultaneously acquired ADF and annular bright-field (ABF) STEM images. Furthermore, the Cramér-Rao lower bound (CRLB) is introduced, i.e. a theoretical lower bound on the variance of any unbiased estimator. This CRLB is used to quantify the precision of the structure parameters of interest, such as the atomic column positions and the integrated atomic column intensities. |
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Language
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English
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Source (journal)
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Advances in imaging and electron physics. - San Diego, Calif.
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Source (book)
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Advances in imaging and electron physics
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Publication
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San Diego, Calif.
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Elsevier
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2021
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ISSN
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1076-5670
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ISBN
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978-0-12-824607-8
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DOI
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10.1016/BS.AIEP.2021.01.002
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Volume/pages
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217
, p. 29-72
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Full text (Publisher's DOI)
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Full text (publisher's version - intranet only)
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