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Proceedings Paper

Image processing and image reconstruction with the use of a-priori information
Author(s): Chin-Tu Chen; Valen E. Johnson; Xiaoping Hu; Wing H. Wong; Charles E. Metz
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Paper Abstract

Bayesian methods that utilize Gibbs priors to incorporate a priori information in the statistical models used for deriving algorithms for image processing and image reconstruction have been developed. The Gibbs prior describes the local continuity of neighboring pixels and takes into account the effect of limited spatial resolution. These new approaches are capable of providing improved image quality. 1.

Paper Details

Date Published: 1 July 1990
PDF: 4 pages
Proc. SPIE 1233, Medical Imaging IV: Image Processing, (1 July 1990); doi: 10.1117/12.18922
Show Author Affiliations
Chin-Tu Chen, Univ. of Chicago (United States)
Valen E. Johnson, Duke Univ. (United States)
Xiaoping Hu, Univ. of Chicago (United States)
Wing H. Wong, Univ. of Chicago (United States)
Charles E. Metz, Univ. of Chicago (United States)

Published in SPIE Proceedings Vol. 1233:
Medical Imaging IV: Image Processing
Murray H. Loew, Editor(s)

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