Date of Award
Doctor of Philosophy (PhD)
Department of Electrical and Computer Engineering
Stephen C. Cain, PhD
This research extends the theory and understanding of the laser speckle imaging technique. This non-traditional imaging technique may be employed to improve space situational awareness and image deep space objects from a ground-based sensor system. The use of this technique is motivated by the ability to overcome aperture size limitations and the distortion effects from Earth’s atmosphere. Laser speckle imaging is a lensless, coherent method for forming two-dimensional images from their autocorrelation functions. Phase retrieval from autocorrelation data is an ill-posed problem where multiple solutions exist. This research introduces polarization diversity as a method for obtaining additional information so the structure of the object being reconstructed can be improved. Results show that in some cases the images restored using polarization diversity are superior to those reconstructed without it. This research presents statistical analysis of the observed data, two distinct image recovery algorithms, and a Cramer-Rao Lower Bound on resolution. A mathematical proof is provided to demonstrate the statistical properties of the observed, noisy autocorrelation data. The algorithms are constructed using the Expectation-Maximization approach and a polarization parameter that relates two independently observed data channels. The algorithms are validated with computer simulation and laboratory experiment. Comparison is made to an existing phase-retrieval technique. The theoretical lower bound is developed for comparing theoretical performance with and without polarization diversity. The results demonstrate the laser speckle imaging technique is improved with polarization diversity.
DTIC Accession Number
Dixon, Donald B., "Statistical Image Recovery from Laser Speckle Patterns with Polarization Diversity" (2010). Theses and Dissertations. 1973.