Denoising and Multivariate Analysis of Time-Of-Flight SIMS Images

Journal Article · Sat Aug 30 00:00:00 EDT 2003 · Surface and Interface Analysis

DOI:https://doi.org/10.1002/sia.1580· OSTI ID:15005247

Wickes, Bronwyn ^[1]; Kim, Y ^[2]; Castner, David G ^[1]

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1. 8408
2. Washington University

Time-of-flight SIMS (ToF-SIMS) imaging offers a modality for simultaneously visualizing the spatial distribution of different surface species. However, the utility of ToF-SIMS datasets may be limited by their large size, degraded mass resolution and low ion counts per pixel. Through denoising and multivariate image analysis, regions of similar chemistries may be differentiated more readily in ToF-SIMS image data. Three established denoising algorithms down-binning, boxcar and wavelet filtering were applied to ToF-SIMS images of different surface geometries and chemistries. The effect of these filters on the performance of principal component analysis (PCA) was evaluated in terms of the capture of important chemical image features in the principal component score images, the quality of the principal component

• Research Organization: Pacific Northwest National Lab., Richland, WA (US), Environmental Molecular Sciences Lab. (US)
• Sponsoring Organization: US Department of Energy (US)
• DOE Contract Number: AC06-76RL01830
• OSTI ID: 15005247
• Journal Information: Surface and Interface Analysis, Journal Name: Surface and Interface Analysis Journal Issue: 8 Vol. 35
• Country of Publication: United States
• Language: English

Related Subjects

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY
ENVIRONMENTAL MOLECULAR SCIENCES LABORATORY
TIME-OF-FLIGHT SECONDARY ION MASS SPECTROMETRY
IMAGES
ION MICROPROBE ANALYSIS
MASS SPECTROSCOPY
MULTIVARIATE ANALYSIS
MULTIVARIATE IMAGE ANALYSIS
MVIA
PCA
PERFORMANCE
PRINCIPAL COMPONENTS ANALYSIS
SIGNAL-TO-NOISE RATIO
TIME-OF-FLIGHT MASS SPECTROMETERS
TOF-SIMS
WAVELET FILTERING