Title: Efficient Iterative Methods for Large Scale Inverse Problems

James Nagy
Mathematic and Computer Science
Emory Univerity
Atlanta, GA

Abstract: Ill-posed problems arise in many image processing
applications,
including microscopy, medicine and astronomy.  Iterative methods are
typically recommended for these large scale problems, but they can be
difficult to use in practice.  In this talk we consider, in
particular, separable nonlinear least squares models.  We discuss the
computational issues involved in working efficiently with the
Jacobian, and a Golub-Kahan based hybrid method used for linear
subproblems.  Applications from image processing illustrate the
effectiveness of the resulting numerical schemes.