Positivity Constraint Implementations for Multiframe Blind Deconvolution ReconstructionsDate: 2014-10-21 Add to Google Calendar
Time: 8:30 am
Location: Holmes Hall 389
Speaker: Paul Billings, candidate for PhD
Reconstruction of imagery degraded by atmospheric turbulence is inherently an ill-posed problem. Multiple solutions can be found which satisfy the measured data to the extent allowed by the noise statistics. The symmetric nature of a spatially invariant imaging system gives rise to an ambiguity between object and distortion. Furthermore, portions of the object spatial frequency information are often attenuated beyond usefulness. Research in this field is primarily concerned with resolving this ambiguity and making a quality estimate of the object in a timely fashion. Many of the more advanced image reconstruction algorithms are iterative algorithms, seeking to minimize error/cost or maximize likelihood/conditional probability. The estimates, of course, are random variables, and regularization and constraints are often employed to guide solutions or reduce effects of overfitting. While positivity is an often employed constraint, one can conceive of various ways to achieve this. We evaluate several functional parameterizations (e.g., squaring the parameters) as well as the use of an optimizer employing search boundaries. Performance is quantified by metrics, including RMS error (spatial domain), RMS phase error curves (spatial frequency domain), and timing to characterize computational demands.
Bio: Paul Billings received a B.S. in electrical engineering, with minors in physics and mathematics, from New Mexico State University in 1992, emphasizing electro-optics. He continued at NMSU and received his M.S. degree in electrical engineering in 1993. Seeking to satisfy his entrepreneurial spirit, he came to Hawaii to start a software company at the newly formed Maui Research and Technology Center. Managing enough work to stay on-island over the years, he eventually returned to his roots, so to speak, when he joined Textron System Corp in 1997 where he performed research in the areas of laser radar imaging, image reconstruction, and 3D imaging. He continues to work for Textron as a senior member of their modeling and simulation group.