Image processing and image reconstruction with the use of a-priori information

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.© (1990) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.