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Proceedings Paper

Deblurring using iterative multiplicative regularization technique
Author(s): Aria Abubakar; Peter M. van den Berg; Tarek M. Habashy; Henning Braunisch
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Paper Abstract

In this work a new deblurring algorithm for a special deconvolution problem, where a parameter describes the degree of blurring, is considered. The algorithm is based on the Conjugate Gradient technique and uses the so-called weighted L2-norm regularizer to obtain a reasonable solution. In order to avoid the necessity of determining the appropriate regularization parameter for this regularizer, this regularizer is included as a multiplicative constraint. In this way, the appropriate regularization parameter will be controlled by the inversion process itself. Numerical testing shows that the proposed algorithm works very effectively.

Paper Details

Date Published: 15 May 2003
PDF: 7 pages
Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); doi: 10.1117/12.480408
Show Author Affiliations
Aria Abubakar, Delft Univ. of Technology (Netherlands)
Peter M. van den Berg, Delft Univ. of Technology (Netherlands)
Tarek M. Habashy, Schlumberger-Doll Research (United States)
Henning Braunisch, Intel Corp. (United States)

Published in SPIE Proceedings Vol. 5032:
Medical Imaging 2003: Image Processing
Milan Sonka; J. Michael Fitzpatrick, Editor(s)

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