Dianne Prost O'Leary
Optimization Methods for Image Deblurring
Wednesday, April 1, 2009
Building 3 Auditorium - 11:00 AM
(Coffee at 10:30 AM)
Since the purpose of deblurring images is to obtain the best possible reconstruction, optimization is fundamental to the process. This talk will survey some of the problems and techniques that lead to good reconstructions, including optimal choice of regularization parameters, criteria for evaluating good reconstructions, and construction and display of confidence intervals for image values.
Dianne Prost O'Leary is a professor of computer science at the University of Maryland,and also holds an appointment in the university's Institute for Advanced Computer Studies (UMIACS) and in the Applied Mathematics and Scientific Computing Program. She earned a B.S. from Purdue University and a Ph.D from Stanford University. Her research is in computational linear algebra and optimization, with applications to solution of ill-posed problems, image deblurring, information retrieval, and quantum computing. She has authored over 90 research publications on numerical analysis and computational science, two books, and 30 publications on education and mentoring. She is a member of SIAM and AWM and a Fellow of the ACM. Further information about her work can be found at http://www.cs.umd.edu/users/oleary
IS&T Colloquium Committee Host: Nargess Memarsadeghi