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Proceedings Paper

Extensions of the cross-referencing method for choosing good regularized solutions to image recovery problems
Author(s): John W. Hilgers; Barbara S. Bertram; Monica M. Alger; William R. Reynolds
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Paper Abstract

It is well known that regularization techniques are often required to obtain stable approximate solutions to ill-posed problems in imaging. Most regularization techniques require the choice of one or more parameters. In previous work, the cross referencing method has proven to be an effective method in obtaining such approximate solutions. It is also true that varying the singular values of the regularization operator independently can provide great improvement in the quality of the regularized solution. In the present paper, we incorporate this idea as an extension to the cross referencing method.

Paper Details

Date Published: 9 December 1997
PDF: 4 pages
Proc. SPIE 3171, Computational, Experimental, and Numerical Methods for Solving Ill-Posed Inverse Imaging Problems: Medical and Nonmedical Applications, (9 December 1997); doi: 10.1117/12.279729
Show Author Affiliations
John W. Hilgers, Signature Research, Inc. and Michigan Technological Univ. (United States)
Barbara S. Bertram, Michigan Technological Univ. (United States)
Monica M. Alger, Michigan Technological Univ. (United States)
William R. Reynolds, Signature Research, Inc. (United States)


Published in SPIE Proceedings Vol. 3171:
Computational, Experimental, and Numerical Methods for Solving Ill-Posed Inverse Imaging Problems: Medical and Nonmedical Applications
Randall Locke Barbour; Mark J. Carvlin; Michael A. Fiddy, Editor(s)

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