Date of Award
Doctor of Philosophy (PhD)
Department of Electrical and Computer Engineering
Stephen C. Cain, PhD
This research presents an algorithm that improves the ability to view objects using an electro-optical imaging system with at least one polarization sensitive channel in addition to the primary channel. An innovative algorithm for detection and estimation of the defocus aberration present in an image is also developed. Using a known defocus aberration, an iterative polarimeter deconvolution algorithm is developed using a generalized expectation-maximization (GEM) model. The polarimeter deconvolution algorithm is extended to an iterative polarimeter multiframe blind deconvolution (PMFBD) algorithm with an unknown aberration. Using both simulated and laboratory images, the results of the new PMFBD algorithm clearly outperforms an RL-based MFBD algorithm. The convergence rate is significantly faster with better fidelity of reproduction of the targets. Clearly, leveraging polarization data in electro-optical imaging systems has the potential to significantly improve the ability to resolve objects and, thus, improve Space Situation Awareness.
DTIC Accession Number
Strong, David M., "Polarimeter Blind Deconvolution Using Image Diversity" (2007). Theses and Dissertations. 2892.