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Testing the success of analytical image correction routines: Surface images
Author(s) -
Barkshire I. R.,
Walton J. M.,
Prutton M.
Publication year - 1993
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.740200707
Subject(s) - image (mathematics) , surface (topology) , computer vision , computer science , artificial intelligence , mathematics , geometry
Multispectral techniques in Auger microscopy involve the acquisition of data as several spatially registered images or signals from the Auger, specimen absorption current, characteristic x‐ray, backscattered and secondary electron signals. Each signal contains information from different interactions and volumes within the sample. Various combinations of these signals can be used along with simple physical models to remove those contrast variations in Auger images that are not due to compositional variations of the sample within the Auger escape depth. Such contrast may, for example, be due to beam current fluctuations during data acquisition, substrate backscattering or topographical effects. To measure the success of these corrections, two tests have been devised: the calculation of the number of resolvable levels in the Auger image before and after correction; and the measurement of the modulus of correlation | C AR | between the corrected Auger image and the correction factor image. The tests may be used to evaluate any new image correction method. They have been applied to simulated and experimental data for a sample with varying subsurface composition. The results show that both tests are useful for evaluating the accuracy of a correction, and that measurement of | C AR | is the more sensitive test.