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Blind deblurring of spiral CT images Based on ENR and Wiener filter

Blind deblurring of spiral CT images Based on ENR and Wiener filter In previous studies, we developed a blind deblurring algorithm based on the edge-to-noise ratio (ENR) and EM algorithm to improve the quality of spiral CT images. In this work, we apply the Wiener filter in place of the EM algorithm to improve the timing performance. The algorithm works well in patient studies. After fully automatic blind deblurring, the conspicuity of the submillimeter features of the cochlea image is substantially improved. The new ENR-Wiener blind deblurring approach significantly improves the computation speed with comparable image quality in previous studies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of X-Ray Science and Technology IOS Press

Blind deblurring of spiral CT images Based on ENR and Wiener filter

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Publisher
IOS Press
Copyright
Copyright © 2005 by IOS Press, Inc
ISSN
0895-3996
eISSN
1095-9114
Publisher site
See Article on Publisher Site

Abstract

In previous studies, we developed a blind deblurring algorithm based on the edge-to-noise ratio (ENR) and EM algorithm to improve the quality of spiral CT images. In this work, we apply the Wiener filter in place of the EM algorithm to improve the timing performance. The algorithm works well in patient studies. After fully automatic blind deblurring, the conspicuity of the submillimeter features of the cochlea image is substantially improved. The new ENR-Wiener blind deblurring approach significantly improves the computation speed with comparable image quality in previous studies.

Journal

Journal of X-Ray Science and TechnologyIOS Press

Published: Jan 1, 2005

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