Molina, Rafael (Molina Porto)Núñez de Murga, Jorge, 1955-Cortijo, Francico JoséMateos López, Javier2009-06-082009-06-0820011053-5888https://hdl.handle.net/2445/8546When preparing an article on image restoration in astronomy, it is obvious that some topics have to be dropped to keep the work at reasonable length. We have decided to concentrate on image and noise models and on the algorithms to find the restoration. Topics like parameter estimation and stopping rules are also commented on. We start by describing the Bayesian paradigm and then proceed to study the noise and blur models used by the astronomical community. Then the prior models used to restore astronomical images are examined. We describe the algorithms used to find the restoration for the most common combinations of degradation and image models. Then we comment on important issues such as acceleration of algorithms, stopping rules, and parameter estimation. We also comment on the huge amount of information available to, and made available by, the astronomical community.19 p.application/pdfeng(c) IEEE, 2001Estadística bayesianaProcessament d'imatgesBayes methodsAstronomy computingImage restorationNoiseImage restoration in astronomy: a Bayesian perspectiveinfo:eu-repo/semantics/article500851info:eu-repo/semantics/openAccess