Optical Power Spectrum Analysis Diffraction Pattern Sampling has matured during the last decade into a technique that now is used routinely by scientists and engineers in a wide range of disciplines. In this paper we discuss recent developments in solid state optical power spectrum analysis systems, nonparametric pattern recognition algorithms and applications of the hardware and software technology. Today's modern diffraction pattern sampler utilizes a solid state photodetector array, wide-band high gain monolithic amplifiers and advanced digital logic circuitry. It is readily interfaced to minicomputers or microcomputers that can control the required Materials Handling both for laboratory and industrial applications. As many as 64 sample point: in the diffraction plane may be easily acquired 500 times per second with this type of system. Thus, gathering large data bases for valid statistical pattern recognition experiments or implementing quality control systems in an industrial environment is relatively easy. Nonparametric feature analysis procedures for sampled diffraction patterns based on ranking, have now evolved and been applied both to classical decision problems and more recently to estimation problems. In addition to using these techniques for evaluating features, procedures based on Mutual Information and Rank Correlation may be used to select optimal subsets from a larger original set of features. Although the over-all feature selection problem is still basically solved by ad hoc procedures, availability of the optimization technique allows a significant amount of evaluation to be done automatically while the user concentrates on developing the specific algorithm examples illustrating the use of the diffraction pattern sampling system and pattern analysis software to solve both decision making and estimation problems are discussed.
Harvey L. Kasdan,
"Optical Power Spectrum Sampling And Algorithms", Proc. SPIE 0117, Data Extraction and Classification from Film, (22 November 1977); doi: 10.1117/12.955658; https://doi.org/10.1117/12.955658