Quantitative statistical analysis, optimization and noise reduction of atomic resolved electron energy loss spectrum images

K. J. Dudeck, M. Couillard, S. Lazar, Christian Dwyer, G. A. Botton

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

In this work we investigate methods of statistical processing and background fitting of atomic resolution electron energy loss spectrum image (SI) data. Application of principal component analysis to SI data has been analyzed in terms of the spectral signal-to-noise ratio (SNR) and was found to improve both the spectral SNR and its standard deviation over the SI, though only the latter was found to improve significantly and consistently across all data sets analyzed. The influence of the number of principal components used in the reconstructed data set on the SNR and resultant elemental maps has been analyzed and the experimental results are compared to theoretical calculations.

Original languageEnglish (US)
Pages (from-to)57-67
Number of pages11
JournalMicron
Volume43
Issue number1
DOIs
StatePublished - Jan 2012
Externally publishedYes

Fingerprint

Signal-To-Noise Ratio
Noise
Electrons
Principal Component Analysis
Datasets

Keywords

  • EELS
  • Principal component analysis
  • Signal-to-noise ratio
  • Spectrum image
  • Strontium titanate

ASJC Scopus subject areas

  • Cell Biology
  • Structural Biology

Cite this

Quantitative statistical analysis, optimization and noise reduction of atomic resolved electron energy loss spectrum images. / Dudeck, K. J.; Couillard, M.; Lazar, S.; Dwyer, Christian; Botton, G. A.

In: Micron, Vol. 43, No. 1, 01.2012, p. 57-67.

Research output: Contribution to journalArticle

Dudeck, K. J. ; Couillard, M. ; Lazar, S. ; Dwyer, Christian ; Botton, G. A. / Quantitative statistical analysis, optimization and noise reduction of atomic resolved electron energy loss spectrum images. In: Micron. 2012 ; Vol. 43, No. 1. pp. 57-67.
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