GlobalBioIm: A Unifying Computational Framework for Solving Inverse Problems

Michael Unser 1 Emmanuel Soubies 1 Ferréol Soulez 2, 1 Michael Mccann 1 Laurène Donati 1
1 Biomedical Imaging Group [Lausanne]
2 CRAL - Centre de Recherche Astrophysique de Lyon
Abstract : We present a unifying framework for the development of state-of-the-art reconstruction algorithms in computational optics with a clear separation between the physical (forward model) and signal-related (regularization, incorporation of prior constraints) aspects of the problem. The pillars of our formulation are: (i) an operator algebra with its set of fast linear solvers, (ii) a variational derivation of reconstruction methods, and (iii) a suite of efficient numerical tools for the resolution of large-scale optimization problems. These core technologies are incorporated into a modular software library featuring the key components for the implementation and testing of iterative reconstruction algorithms. The concept is illustrated with concrete examples in 3D deconvolution microscopy and lenseless imaging.
Type de document :
Communication dans un congrès
OSA Imaging and Applied Optics Congress on Computational Optical Sensing and Imaging (COSI'17), 2017, San Francisco, United States. OSA Technical Digest
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Contributeur : Ferréol Soulez <>
Soumis le : lundi 13 novembre 2017 - 15:31:49
Dernière modification le : mardi 26 mars 2019 - 01:16:51

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  • HAL Id : insu-01632807, version 1

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CRAL | ENS-LYON | UNIV-LYON1 | INSU

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Michael Unser, Emmanuel Soubies, Ferréol Soulez, Michael Mccann, Laurène Donati. GlobalBioIm: A Unifying Computational Framework for Solving Inverse Problems. OSA Imaging and Applied Optics Congress on Computational Optical Sensing and Imaging (COSI'17), 2017, San Francisco, United States. OSA Technical Digest. 〈insu-01632807〉

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