Deblurring using iterative multiplicative regularization technique

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

doi:10.1117/12.480408

15 May 2003 Deblurring using iterative multiplicative regularization technique

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

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.

Citation Download Citation

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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