Microsc. Microanal. Microstruct. 2, 245-256 (1991)
DOI: 10.1051/mmm:0199100202-3024500

Automated processing of parallel-detection EELS data

Michael K. Kundmann et Ondrej L. Krivanek

Gatan R&D, 6678 Owens Drive, Pleasanton, CA 94588, U.S.A.

Abstract
An algorithm for automatic detection and identification of edges in an EELS spectrum is presented. It has the following features: 1) it compresses the dynamic range of EELS spectra and enhances the ionization edge signals via difference transforms, 2) it removes residual background, thereby isolating sharp features associated with the edge thresholds and noise, 3) it distinguishes true edge-threshold features from noise via statistical analysis. In addition to paving the way for rapid, automated EELS elemental analysis, the algorithm is capable of detecting edges which are easily overlooked by human analysts.

PACS
0705K - Data analysis: algorithms and implementation; data management.
0781 - Electron and ion spectrometers.
8280 - Chemical analysis and related physical methods of analysis.

Key words
EEL spectroscopy -- Statistical method -- Algorithm -- Difference calculus -- Automated processing -- Data analysis -- Automatic detection -- Ionization edge


© EDP Sciences 1991