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Maximum Pixel Spectrum: A New Tool For Detecting And Recovering Rare, Unanticipated Features From Spectrum Image Data Cubes

Published

Author(s)

David S. Bright, Dale E. Newbury

Abstract

A new software tool, the Maximum Pixel Spectrum detects rare events within a spectrum image data cube, such as that generated with electron-excited energy dispersive x-ray spectrometry (EDS) in a scanning electron microscope. The Maximum Pixel Spectrum is a linear array of intensity versus channel value (photon energy), where the intensity is the maximum value within earch x-ray energy plane of the data cube. For EDS data, this pseudo-spectrum has the principal characteristics of a real spectrum so that x-ray peaks corresponding to highly localized trace constituents or foreign contaminants, even those that are confined to one pixel of the image, can be seen at a glance, when the Maximum Channel Spectrum is compared to the Summation Spectrum. The Summation Spectrum is a linear array where the summation of all channels within each energy plane gives the intensity value versus photon energy. The Summation Spectrum is sensitive to the dominant features of the data cube.
Citation
Journal of Microscopy-Oxford
Volume
216
Issue
No. 2

Keywords

data cubes, data mining, electron probe x-ray microanalysis (EPMA, energy dispersive x-ray spectrometry (ED, image processing, Maximum Channel Spectrum, scanning electron microscopy (SEM, spectrum imaging, Summation Spectrum

Citation

Bright, D. and Newbury, D. (2004), Maximum Pixel Spectrum: A New Tool For Detecting And Recovering Rare, Unanticipated Features From Spectrum Image Data Cubes, Journal of Microscopy-Oxford (Accessed May 14, 2021)
Created November 1, 2004, Updated February 19, 2017