New method of multispectral image post-processing based on an instrument model for high contrast imaging systems : Application to exoplanet detection

This research focuses on high contrast multispectral imaging in the view of directly detecting and characterizing Exoplanets. In this framework, the development of innovative image post-processing methods is essential in order to eliminate the quasi-static speckles in the final image, which remain the main limitation for high contrast. Even though the residual instrumental aberrations are responsible for these speckles, no post-processing method currently uses a model of coronagraphic imaging, which takes these aberrations as parameters. The research approach adopted includes the development of a method, in a Bayesian Framework, based on an analytical coronagraphic imaging model and an inversion algorithm, to estimate jointly the instrumental aberrations and the object of interest, i.e. the exoplanets, in order to separate properly these two contributions. The instrumental aberration estimation directly from focal plane images, also named phase retrieval, is the most difficult step because the model of on-axis instrumental response, of which these aberrations depend on, is highly non-linear. The development and the study of an approximate model of coronagraphic imaging thus proved very useful to understand the problem at hand and inspired me some minimization strategies. I finally tested my method and estimated its performances in terms of robustness and exoplanets detection. For this, I applied it to simulated images and I studied the effect of the different parameters of the imaging model I used. The findings from this research provide evidence that this method, in association with an optimization scheme based on a good knowledge of the problem at hand, can operate in a relatively robust way, despite the difficulties of the phase retrieval step. In particular, it allows the detection of exoplanets in the case of simulated images with a detection level compliant with the goal of the SPHERE instrument. The next steps will be to verify the efficiency of this new method on simulated images using more realistic coronagraphs and on real images from the SPHERE instrument. In addition, the extension of the method for the characterization of exoplanets is relatively easy, as its extension to the study of larger objects such as circumstellar disks. Finally, the results of this work will also bring some crucial insights for the development of future instruments. In particular, the Extremely Large Telescopes have already risen some technical challenges for the next generation of planet finders, which may partly be addressed by an image processing method based on an imaging model.

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Source https://theses.hal.science/tel-00843202
Author Ygouf, Marie
Maintainer CCSD
Last Updated May 10, 2026, 09:49 (UTC)
Created May 10, 2026, 09:49 (UTC)
Identifier NNT: 2012GRENY100
Language fr
Rights https://about.hal.science/hal-authorisation-v1/
contributor Institut de Planétologie et d'Astrophysique de Grenoble (IPAG) ; Observatoire des Sciences de l'Univers de Grenoble (OSUG) ; Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)
creator Ygouf, Marie
date 2012-12-06T00:00:00
harvest_object_id 56365a06-8726-4cf8-95fd-f0b4b2e544e8
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2026-03-31T00:00:00
set_spec type:THESE