Large-Scale Inverse Problems in Imaging

Applied and Computational Mathematics Seminar
Monday, March 1, 2010 - 13:00
1 hour (actually 50 minutes)
Skiles 255
Mathematics and Computer Science, Emory University
Large-scale inverse problems arise in a variety of importantapplications in image processing, and efficient regularization methodsare needed to compute meaningful solutions.  Much progress has beenmade in the field of large-scale inverse problems, but many challengesstill remain for future research.  In this talk we describe threecommon mathematical models including a linear, a separable nonlinear,and a general nonlinear model. Techniques for regularization andlarge-scale implementations are considered, with particular focusgiven to algorithms and computations that can exploit structure in theproblem. Examples will illustrate the properties of these algorithms.