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Méthodes pour l'analyse des champs profonds extragalactiques MUSE : démélange et fusion de données hyperspectrales ;détection de sources étendues par inférence à grande échelle

Abstract : This work takes place in the context of the study of hyperspectral deep fields produced by the European 3D spectrograph MUSE. These fields allow to explore the young remote Universe and to study the physical and chemical properties of the first galactical and extra-galactical structures.The first part of the thesis deals with the estimation of a spectral signature for each galaxy. As MUSE is a terrestrial instrument, the atmospheric turbulences strongly degrades the spatial resolution power of the instrument thus generating spectral mixing of multiple sources. To remove this issue, data fusion approaches, based on a linear mixing model and complementary data from the Hubble Space Telescope are proposed, allowing the spectral separation of the sources.The second goal of this thesis is to detect the Circum-Galactic Medium (CGM). This CGM, which is formed of clouds of gas surrounding some galaxies, is characterized by a spatially extended faint spectral signature. To detect this kind of signal, an hypothesis testing approach is proposed, based on a max-test strategy on a dictionary. The test statistics is learned on the data. This method is then extended to better take into account the spatial structure of the targets, thus improving the detection power, while still ensuring global error control.All these developments are integrated in the software library of the MUSE consortium in order to be used by the astrophysical community.Moreover, these works can easily be extended beyond MUSE data to other application fields that need faint extended source detection and source separation methods.
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Raphael Bacher. Méthodes pour l'analyse des champs profonds extragalactiques MUSE : démélange et fusion de données hyperspectrales ;détection de sources étendues par inférence à grande échelle. Traitement du signal et de l'image [eess.SP]. Université Grenoble Alpes, 2017. Français. ⟨NNT : 2017GREAT067⟩. ⟨tel-01727498v2⟩

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