Computer Science – Information Theory
Scientific paper
May 2001
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2001aipc..568..493n&link_type=abstract
BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: 20th International Workshop. AIP Conference Proceedi
Computer Science
Information Theory
Image Processing, Inference Methods, Information Theory And Communication Theory
Scientific paper
In this paper we propose a method for restoring gammagraphic images. The method is based on a Bayesian estimator containing a compound regularizer. This method allows to take into account all gammagraphic image characteristics (such as positive radio-isotope distribution blurred by photon scattering and degraded by Poisson noise). Moreover the compound regularizer is constructed so that the estimator satisfies several desirable analytical and computational properties including uniqueness, stability, scale invariance and efficient implementation. .
Faye Christian
Guillemin Herve
Nguyen Mai K.
Truong Tuyen Trung
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