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Caractérisation multibande de galaxies par hiérarchie de modèles et arbres de composantes connexes

Abstract : This thesis proposes a morphological and multiband characterization method for galaxies. Galaxies started to evolve and interact since the very beginning of the Universe and they now present a large variety of appearance. Their shapes in the different spectral bands are thus an important clue to understand the history of the Universe. This work develops a high semantic level galactic characterization based on decompositions into astrophysical structures which can be easily interpreted by the astronomers. The decomposition scheme is based on a hierarchy of models going from the description of dominant structures (bulge and disc) to the finest components (spiral arms, rings, ...). The proposed models are completed by an adaptive filter on the observation whose parameters are estimated jointly with those of the galactic structures. The estimation of the model parameters are performed in a Bayesian context by using stochastic algorithms (Markov Chain Monte Carlo algorithms). The speed of the algorithms is increased by the use of adaptive scales and directions methods, as well as a multi-temperature simulated annealing. Moreover, theoretical developments of the theory of connected component trees enable the conception of robust and efficient non-parametric multiband algorithms for the mandatory pre-processing of the images. Advances on the theory of hyper-connections and associated hyper-connected components trees were developed for this purpose. The performance of the proposed approach has been validated on about 1 500 multiband images of galaxies. The results show that it is both efficient and robust. This new characterization method can now be used as a basis to discover a new spectro-morphological galaxy classification scheme.
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https://tel.archives-ouvertes.fr/tel-00559584
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Submitted on : Tuesday, January 25, 2011 - 9:30:23 PM
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Benjamin Perret. Caractérisation multibande de galaxies par hiérarchie de modèles et arbres de composantes connexes. Traitement du signal et de l'image [eess.SP]. Université de Strasbourg, 2010. Français. ⟨tel-00559584⟩

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