ENTROPY AND INFORMATION IN THE DESIGN AND ANALYSIS OF IMAGING SYSTEMS.
KeywordsImaging systems -- Design.
Entropy (Information theory)
Optical data processing -- Mathematical models.
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PublisherThe University of Arizona.
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AbstractThe main thrust of this dissertation is the application of statistics and information theory to design, analysis and estimation pertaining to image-forming systems. This study explores the application of Shannon's information in pupil design, the characterization of noise, and study of its behavior in a specific electro-optical system, and estimation of the degraded spread function in atmospherical imagery using the maximum entropy method. Our study shows that a pupil designed to maximize Shannon's information throughput is an apodizer, resulting in resolution and contrast enhancement when compared to the diffraction-limited case. The Strehl ratio is about 0.55. Investigation of statistical and spectral properties as a function of gray level in an electro-optical tracking system indicates that the noise is "white," having a wide band and a close-to-Gaussian distribution. Estimating the spread function via maximum entropy technique has revealed some remarkable results. Using an edge as the object, simulation studies predict a superior estimate in the mean squared error sense to those of the least squares in the presence of three types of noise (signal-dependent Gaussian and Poisson, and signal-independent Gaussian noise). Information theory, linear systems theory, sampling theory and more particularly, statistics and the Fast Fourier Transform are used to derive our results.
Degree ProgramOptical Sciences