Paper
21 March 1989 Statistical Analysis Of Random And Pseudo Random Rough Surfaces
Monique Rasigni, Georges Rasigni, Francoise Varnier, Christophe Dussert, Jacqueline Palmari, Nicole Mayani, Antoine Llebaria
Author Affiliations +
Proceedings Volume 1009, Surface Measurement and Characterization; (1989) https://doi.org/10.1117/12.949157
Event: 1988 International Congress on Optical Science and Engineering, 1988, Hamburg, Germany
Abstract
For many years we have developed a method to reconstruct the profiles of statistically rough surfaces. This method is based on a microdensitometer analysis of electron micrographs of shadowed surface replicas. From the quantized profiles it is possible to compute the statistical moments -particularly the second order one called autocovariance function (ACF)- that characterize the surface. In general ACF's for pseudorandom surfaces are not decreasing monotonic functions and some complications arise when the definition of a auto-covariance length for those surfaces is considered. Solutions are proposed to overcome them; in particular, it seems preferable to deduce certain statistical parameters from the spectrum instead of the ACF. Moreover a new approach based on the minimal spanning tree (MST) -which is a graph constructed on the set of points representing the position of features on a surface- is proposed to study statistically order and disorder in the distribu-tion of these features.
© (1989) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Monique Rasigni, Georges Rasigni, Francoise Varnier, Christophe Dussert, Jacqueline Palmari, Nicole Mayani, and Antoine Llebaria "Statistical Analysis Of Random And Pseudo Random Rough Surfaces", Proc. SPIE 1009, Surface Measurement and Characterization, (21 March 1989); https://doi.org/10.1117/12.949157
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Cited by 3 scholarly publications.
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KEYWORDS
Photomicroscopy

Laser induced fluorescence

Statistical analysis

Gold

Particles

Scattering

Thin films

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