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Data scaling for quantitative imaging XPS
Author(s) -
Walton John,
Fairley Neal
Publication year - 2009
Publication title -
surface and interface analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 90
eISSN - 1096-9918
pISSN - 0142-2421
DOI - 10.1002/sia.2974
Subject(s) - scaling , square root , poisson distribution , root mean square , multivariate statistics , x ray photoelectron spectroscopy , noise (video) , data set , computer science , variance (accounting) , shot noise , set (abstract data type) , statistics , algorithm , data mining , mathematics , image (mathematics) , artificial intelligence , physics , engineering , telecommunications , electrical engineering , geometry , accounting , nuclear magnetic resonance , detector , business , programming language
XPS spectrum image data sets acquired on laboratory instruments have inherently poor signal/noise, and require the use of multivariate analytical techniques to avoid prohibitively long acquisition times. However, when procedures that order the data by variance are used, the data set must be scaled beforehand, since it has a Poisson distribution. Different scaling methods may be used, but their effectiveness in allowing a separation of the chemical information from the noise is critical if loss of information is to be avoided. The performance of three methods, square root, root mean square and optimal scaling, has been compared, and their effectiveness for quantitative photoelectron spectromicroscopy is discussed. Copyright © 2008 John Wiley & Sons, Ltd.