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GlobalBioIm: A Unifying Computational Framework for Solving Inverse Problems

M. Unser, E. Soubies, F. Soulez, M. McCann, L. Donati

Proceedings of the OSA Imaging and Applied Optics Congress on Computational Optical Sensing and Imaging (COSI'17), San Francisco CA, USA, June 26-29, 2017, paper no. CTu1B.

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.

AUTHOR="Unser, M. and Soubies, E. and Soulez, F. and McCann, M. and
        Donati, L.",
TITLE="{GlobalBioIm}: {A} Unifying Computational Framework for Solving
        Inverse Problems",
BOOKTITLE="Proceedings of the {OSA} Imaging and Applied Optics Congress
        on Computational  Optical Sensing and Imaging ({COSI'17})",
address="San Francisco CA, USA",
month="June 26-29,",
note="paper no.\ CTu1B")

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