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Approches "problèmes inverses" régularisées pour l'imagerie sans lentille et la microscopie holographique en ligne

Abstract : In Digital Imaging, the regularized inverse problems methods reconstruct particular information from measurements and an image formation model. With an inverse problem that is ill-posed and ill­conditioned, and with the used image formation mode! having few constraints, it is necessary to introduce a priori conditions in order to restrict ambiguity for the inversion. This allows us to guide the reconstruction towards a satisfying solution. The works of the following thesis delve into the development of reconstruction algorithms of digital holograms based on large-scale optimization methods (smooth and non-smooth). This general framework allowed us to propose different approaches adapted to the challenges found with this unconventional imaging technique: the super-resolution, reconstruction outside the sensor's field, the color holography and finally, the quantitative reconstruction of phase abjects (i.e. transparent). For this last case, the reconstruction problem consists of estimating the complex 2D transmittance of abjects having absorbed and/or dephased the light wave during the recording of the hologram. The proposed methods are validated with the help of numerical simulations that are then applied on experimental data taken from the lensless imaging or from the in-line holographie microscopy (coherent imaging in transmission, with a microscope abject glass). The applications range from the reconstruction of opaque resolution sights, to the reconstruction of biological objects (bacteria), passing through the reconstruction of evaporating ether droplets from a perspective of turbulence study in fluid mechanics.
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Submitted on : Tuesday, October 15, 2019 - 9:34:21 AM
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  • HAL Id : tel-02316039, version 1


Frederic Jolivet. Approches "problèmes inverses" régularisées pour l'imagerie sans lentille et la microscopie holographique en ligne. Imagerie médicale. Université de Lyon, 2018. Français. ⟨NNT : 2018LYSES012⟩. ⟨tel-02316039⟩



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