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Statistical and numerical optimization for speckle blind structured illumination microscopy

Abstract : Conventional structured illumination microscopy (SIM) can surpass the resolution limit inoptical microscopy caused by the diffraction effect, through illuminating the object with a set of perfectly known harmonic patterns. However, controlling the illumination patterns is a difficult task. Even worse, strongdistortions of the light grid can be induced by the sample within the investigated volume, which may give rise to strong artifacts in SIM reconstructed images. Recently, blind-SIM strategies were proposed, whereimages are acquired through unknown, non-harmonic,speckle illumination patterns, which are much easier to generate in practice. The super-resolution capacity of such approaches was observed, although it was not well understood theoretically. This thesis presents two new reconstruction methods in SIM using unknown speckle patterns (blind-speckle-SIM): one joint reconstruction approach and one marginal reconstruction approach. In the joint reconstruction approach, we estimate the object and the speckle patterns together by considering a basis pursuit denoising (BPDN) model with lp,q-norm regularization, with p=>1 and 0
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Submitted on : Tuesday, January 8, 2019 - 2:03:05 PM
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  • HAL Id : tel-01973622, version 1


Penghuan Liu. Statistical and numerical optimization for speckle blind structured illumination microscopy. Optics / Photonic. École centrale de Nantes, 2018. English. ⟨NNT : 2018ECDN0008⟩. ⟨tel-01973622⟩



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