Estimating hyperparameters and instrument parameters in regularized inversion. Illustration for SPIRE/Herschel map making

Autor:	Orieux, F., Giovannelli, J. -F., Rodet, T., Abergel, A.
Rok vydání:	2012
Předmět:	Astrophysics - Instrumentation and Methods for Astrophysics Computer Science - Numerical Analysis Statistics - Applications Statistics - Methodology
Druh dokumentu:	Working Paper
Popis:	We describe regularized methods for image reconstruction and focus on the question of hyperparameter and instrument parameter estimation, i.e. unsupervised and myopic problems. We developed a Bayesian framework that is based on the \post density for all unknown quantities, given the observations. This density is explored by a Markov Chain Monte-Carlo sampling technique based on a Gibbs loop and including a Metropolis-Hastings step. The numerical evaluation relies on the SPIRE instrument of the Herschel observatory. Using simulated and real observations, we show that the hyperparameters and instrument parameters are correctly estimated, which opens up many perspectives for imaging in astrophysics.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1211.3603 Zobrazit plný text záznamu View this record from Arxiv