Deblurring using iterative multiplicative regularization technique

Aria Abubakar; Peter M. van den Berg; Tarek M. Habashy; Henning Braunisch

doi:10.1117/12.480408

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15 May 2003 Deblurring using iterative multiplicative regularization technique

Aria Abubakar, Peter M. van den Berg, Tarek M. Habashy, Henning Braunisch

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Proceedings Volume 5032, Medical Imaging 2003: Image Processing; (2003) https://doi.org/10.1117/12.480408
Event: Medical Imaging 2003, 2003, San Diego, California, United States

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.

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Aria Abubakar, Peter M. van den Berg, Tarek M. Habashy, and Henning Braunisch "Deblurring using iterative multiplicative regularization technique", Proc. SPIE 5032, Medical Imaging 2003: Image Processing, (15 May 2003); https://doi.org/10.1117/12.480408

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