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Comparison of Iterative Methods for some Inverse Problems in Imaging
by
Robert Plemmons
Wake Forest University, Departments of Math & Computer Science, Winston-Salem, NC 27109, USA
In this talk we study and compare a variety of techniques for solving certain ill-posed inverse problems in restoring imagery that has been degraded by noise and blur. Our specific applications include ground-based astronomical imaging as well as the problem of extending depth of focus in near-field optical-digital imaging systems. The main approaches studied involve FFT-based preconditioned conjugate gradient methods with nonnegativity constraints. Test results in applying both linear and nonlinear techniques to restoring both simulated and real data are presented and analyzed.
Date received: March 21, 2001
Copyright © 2001 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Mathematical Conference Abstracts. Document # cagm-30.