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Proceedings Paper

Preconditioners for linear systems arising in image reconstruction
Author(s): Kyle Riley; Curtis R. Vogel
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Paper Abstract

For the numerical solution of large linear systems, the preconditioned conjugate gradient algorithm can be very effective if one has a good preconditioner. Two distinctly different approaches to preconditioning are discussed for solving systems derived from continuous linear operators of the form K + (alpha) L, where K is a convolution operator, L is a regularization operator, and (alpha) is a small positive parameter. The first approach is circulant preconditioning. The second, less standard, approach is based on a two-level decomposition of the solution space. A comparison of the two approaches is given for a model problem arising in atmospheric image deblurring.

Paper Details

Date Published: 2 October 1998
PDF: 9 pages
Proc. SPIE 3461, Advanced Signal Processing Algorithms, Architectures, and Implementations VIII, (2 October 1998); doi: 10.1117/12.325697
Show Author Affiliations
Kyle Riley, Montana State Univ. (United States)
Curtis R. Vogel, Montana State Univ. (United States)


Published in SPIE Proceedings Vol. 3461:
Advanced Signal Processing Algorithms, Architectures, and Implementations VIII
Franklin T. Luk, Editor(s)

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