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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.
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Submitted on : Monday, November 13, 2017 - 3:31:49 PM
Last modification on : Friday, June 11, 2021 - 7:44:02 PM

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  • HAL Id : insu-01632807, version 1

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CNRS | CRAL | UNIV-LYON1 | INSU | ENS-LYON | UDL

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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. ⟨insu-01632807⟩

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