Blind deconvolution is a particularly challenging inverse problem since information on both the desired target and the acquisition system have to be inferred from the measured data. When the collected data are affected by Poisson noise, this problem is typically addressed by the minimization of the Kullback-Leibler divergence, in which the unknowns are sought in particular feasible sets depending on the a priori information provided by the specific application. If these sets are separated, then the resulting constrained minimization problem can be addressed with an inexact alternating strategy. In this paper we apply this optimization tool to the problem of reconstructing astronomical images from adaptive optics systems, and we show that the proposed approach succeeds in providing very good results in the blind deconvolution of nondense stellar clusters.

An alternating minimization method for blind deconvolution from Poisson data / Prato, Marco; A., La Camera; Bonettini, Silvia. - In: JOURNAL OF PHYSICS. CONFERENCE SERIES. - ISSN 1742-6596. - ELETTRONICO. - 542:1(2014), p. 012006. (Intervento presentato al convegno 4th International Workshop on New Computational Methods for Inverse Problems, NCMIP 2014 tenutosi a Cachan nel 23 maggio 2014) [10.1088/1742-6596/542/1/012006].

An alternating minimization method for blind deconvolution from Poisson data

PRATO, Marco;BONETTINI, Silvia
2014

Abstract

Blind deconvolution is a particularly challenging inverse problem since information on both the desired target and the acquisition system have to be inferred from the measured data. When the collected data are affected by Poisson noise, this problem is typically addressed by the minimization of the Kullback-Leibler divergence, in which the unknowns are sought in particular feasible sets depending on the a priori information provided by the specific application. If these sets are separated, then the resulting constrained minimization problem can be addressed with an inexact alternating strategy. In this paper we apply this optimization tool to the problem of reconstructing astronomical images from adaptive optics systems, and we show that the proposed approach succeeds in providing very good results in the blind deconvolution of nondense stellar clusters.
2014
4th International Workshop on New Computational Methods for Inverse Problems, NCMIP 2014
Cachan
23 maggio 2014
542
012006
Prato, Marco; A., La Camera; Bonettini, Silvia
An alternating minimization method for blind deconvolution from Poisson data / Prato, Marco; A., La Camera; Bonettini, Silvia. - In: JOURNAL OF PHYSICS. CONFERENCE SERIES. - ISSN 1742-6596. - ELETTRONICO. - 542:1(2014), p. 012006. (Intervento presentato al convegno 4th International Workshop on New Computational Methods for Inverse Problems, NCMIP 2014 tenutosi a Cachan nel 23 maggio 2014) [10.1088/1742-6596/542/1/012006].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1009714
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