CS700:Graduate Seminar in Computer Science & Informatics

Large Scale Inverse Problems in Imaging

Large scale inverse problems are ubiquitous in imaging applications. An example problem in image deblurring is given, which illustrates some of the difficulties in solving inverse problems. Next we will look at solving linear inverse problems iteratively. A suite of iterative solvers for linear inverse problems is presented, which has been written utilizing the Trilinos framework. To illustrate the use of the solvers, an application for reducing movement degradation of PET brain scans is described. Removing these blurs through computational post-processing requires solving a large, sparse linear inverse problem.
Sarah Knepper is a Ph.D. student in the Computer Science and Informatics Program at Emory University. Her research interests include image processing, high performance computing, and more broadly computational mathematics.