Local smoothness maps: a new method for solving inverse problems with the accurate recovery of sharp gradients

Roumeliotis, G

dc.contributor.author	Roumeliotis, G	en
dc.date.accessioned	2014-03-01T01:45:38Z
dc.date.available	2014-03-01T01:45:38Z
dc.date.issued	1997	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/24671
dc.subject	bayesian approach	en
dc.subject	Inverse Problem	en
dc.subject	Smoothing Parameter	en
dc.title	Local smoothness maps: a new method for solving inverse problems with the accurate recovery of sharp gradients	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/78.611224	en
heal.identifier.secondary	http://dx.doi.org/10.1109/78.611224	en
heal.publicationDate	1997	en
heal.abstract	We describe a novel Bayesian approach to solving inverse problems by simultaneously estimating the reconstructed signal and the local smoothness map (LSM), which is a generalization of the global smoothness parameter that is often used to stabilize inverse problems. The greater flexibility afforded by the introduction of the local smoothness map makes the new method very effective on inverse problems	en
heal.journalName	IEEE Transactions on Signal Processing	en
dc.identifier.doi	10.1109/78.611224	en