Sparse stochastic processes and discretization of linear inverse problems

We present a novel statistically-based discretization paradigm and derive a class of maximum a posteriori (MAP) estimators for solving ill-conditioned linear inverse problems. We are guided by the theory of sparse stochastic processes, which specifies continuous-domain signals as solutions of linear...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 22(2013), 7 vom: 01. Juli, Seite 2699-710
1. Verfasser:	Bostan, Emrah (VerfasserIn)
Weitere Verfasser:	Kamilov, Ulugbek S, Nilchian, Masih, Unser, Michael
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2013
Zugriff auf das übergeordnete Werk:	IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:	Journal Article Research Support, Non-U.S. Gov't