Abstract
Developments in X‐ray photoelectron spectroscopy (XPS) instrumentation and the need for spatial information in surface characterization have led to advances in XPS imaging and related image processing techniques. In this Insight Note, we demonstrate the use of summary statistics as simple, but effective, tools for understanding XPS hyperspectral images (data cubes) prior to more advanced image processing. An XPS image obtained from a silicon surface patterned with different thicknesses of oxide was analyzed with three summary statistics: a tool in the MATLAB programming environment, the mean, and pattern recognition entropy (PRE). The MATLAB tool largely separates the spectra into two groups. The mean does a somewhat better job differentiating between the spectra, and PRE is even more effective. The results of the MATLAB summary statistic are confirmed by plotting the average and standard deviation spectra of different regions of the image it produces. The results of the mean and PRE summary statistics are confirmed by evenly segmenting the results and examining the average and standard deviation spectra of these segments. Fitting these average spectra demonstrates the greater effectiveness of the PRE summary statistic in segmenting the spectra into chemically distinct groups.
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