Recently, Poisson noise has become of great interest in many imaging applications. When regularization strategies are used in the so-called Bayesian approach, a relevant, issue is to find rules for selecting 1 proper value of the regularization parameter. In this work we compare three different approaches which deal with this topic. The first model anus to find the root of a discrepancy equation, while the second one estimates such parameter by adopting a constrained approach. These two models do not always provide reliable results in presence of low counts images. The third approach presented is the inexact Bregman procedure, which allows to use an overestimation of the regularization parameter and moreover enables to obtain very promising results in case of low counts images and High Dynamic Range astronomical images.

Image regularization for Poisson data / A. Benfenati, V. Ruggiero. - In: JOURNAL OF PHYSICS. CONFERENCE SERIES. - ISSN 1742-6588. - 657:1(2015), pp. 012011.1-012011.7. ((Intervento presentato al 5. convegno International Workshop on New Computational Methods for Inverse Problems (NCMIP) tenutosi a Cachan nel 2015 [10.1088/1742-6596/657/1/012011].

Image regularization for Poisson data

A. Benfenati;
2015

Abstract

Recently, Poisson noise has become of great interest in many imaging applications. When regularization strategies are used in the so-called Bayesian approach, a relevant, issue is to find rules for selecting 1 proper value of the regularization parameter. In this work we compare three different approaches which deal with this topic. The first model anus to find the root of a discrepancy equation, while the second one estimates such parameter by adopting a constrained approach. These two models do not always provide reliable results in presence of low counts images. The third approach presented is the inexact Bregman procedure, which allows to use an overestimation of the regularization parameter and moreover enables to obtain very promising results in case of low counts images and High Dynamic Range astronomical images.
Settore MAT/08 - Analisi Numerica
Ecole Normale Superieure Cachan
http://www.iop.org/EJ/journal/conf
https://air.unimi.it/handle/2434/657544
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/657544
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