Aims. High-dynamic range images of astrophysical objects present some difficulties in their restoration because of the presence of very bright point-wise sources surrounded by faint and smooth structures. We propose a method that enables the restoration of this kind of images by taking these kinds of sources into account and, at the same time, improving the contrast enhancement in the final image. Moreover, the proposed approach can help to detect the position of the bright sources. Methods. The classical variational scheme in the presence of Poisson noise aims to find the minimum of a functional compound of the generalized Kullback-Leibler function and a regularization functional: the latter function is employed to preserve some characteristic in the restored image. The inexact Bregman procedure substitutes the regularization function with its inexact Bregman distance. This proposed scheme allows us to take under control the level of inexactness arising in the computed solution and permits us to employ an overestimation of the regularization parameter (which balances the trade-off between the Kullback-Leibler and the Bregman distance). This aspect is fundamental, since the estimation of this kind of parameter is very difficult in the presence of Poisson noise. Results. The inexact Bregman procedure is tested on a bright unresolved binary star with a faint circumstellar environment. When the sources' position is exactly known, this scheme provides us with very satisfactory results. In case of inexact knowledge of the sources' position, it can in addition give some useful information on the true positions. Finally, the inexact Bregman scheme can be also used when information about the binary star's position concerns a connected region instead of isolated pixels.

Deconvolution of post-adaptive optics images of faint circumstellar environments by means of the inexact Bregman procedure / A. Benfenati, A. La Camera, M. Carbillet. - In: ASTRONOMY & ASTROPHYSICS. - ISSN 0004-6361. - 586(2016 Feb). [10.1051/0004-6361/201526960]

Deconvolution of post-adaptive optics images of faint circumstellar environments by means of the inexact Bregman procedure

A. Benfenati
Primo
;
2016

Abstract

Aims. High-dynamic range images of astrophysical objects present some difficulties in their restoration because of the presence of very bright point-wise sources surrounded by faint and smooth structures. We propose a method that enables the restoration of this kind of images by taking these kinds of sources into account and, at the same time, improving the contrast enhancement in the final image. Moreover, the proposed approach can help to detect the position of the bright sources. Methods. The classical variational scheme in the presence of Poisson noise aims to find the minimum of a functional compound of the generalized Kullback-Leibler function and a regularization functional: the latter function is employed to preserve some characteristic in the restored image. The inexact Bregman procedure substitutes the regularization function with its inexact Bregman distance. This proposed scheme allows us to take under control the level of inexactness arising in the computed solution and permits us to employ an overestimation of the regularization parameter (which balances the trade-off between the Kullback-Leibler and the Bregman distance). This aspect is fundamental, since the estimation of this kind of parameter is very difficult in the presence of Poisson noise. Results. The inexact Bregman procedure is tested on a bright unresolved binary star with a faint circumstellar environment. When the sources' position is exactly known, this scheme provides us with very satisfactory results. In case of inexact knowledge of the sources' position, it can in addition give some useful information on the true positions. Finally, the inexact Bregman scheme can be also used when information about the binary star's position concerns a connected region instead of isolated pixels.
Methods: data analysis; Methods: numerical; Techniques: high angular resolution; Techniques: image processing
Settore MAT/08 - Analisi Numerica
Article (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/652729
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