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Reconstruction de spectres-images STEM-EELS partiellement échantillonnés

Abstract : Over the last decade, the application of compressed detection algorithms for tomography has been developed [1,2]. Because of data sparsity, the alignment of tilt series is a major problem. Standard alignment algorithms based on fiducials or automatic feature recognition cannot be used on sparse data. Therefore, as long as the problem of sparse data alignment is not solved, the use of compressed sensing for tomography reconstruction will be limited.
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Submitted on : Friday, December 6, 2019 - 3:19:32 PM
Last modification on : Monday, July 4, 2022 - 9:32:58 AM
Long-term archiving on: : Saturday, March 7, 2020 - 4:02:08 PM


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  • HAL Id : hal-02397455, version 1
  • OATAO : 25046


Etienne Monier, Thomas Oberlin, Nathalie Brun, Marcel Tencé, Marta de Frutos, et al.. Reconstruction de spectres-images STEM-EELS partiellement échantillonnés. 16e Colloque de la Société Française des Microscopies (SFU 2019), Jul 2019, Poitiers, France. pp.74-75. ⟨hal-02397455⟩



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