Kürüm, Ulas, Wiecha, Peter R., French, Rebecca and Muskens, Otto L. (2019) Deep learning enabled real time speckle recognition and hyperspectral imaging using a multimode fiber array. Optics Express, 27 (15), 20965-20979. (doi:10.1364/OE.27.020965).
Abstract
We demonstrate the use of deep learning for fast spectral deconstruction of speckle patterns. The artificial neural network can be effectively trained using numerically constructed multispectral datasets taken from a measured spectral transmission matrix. Optimized neural networks trained on these datasets achieve reliable reconstruction of both discrete and continuous spectra from a monochromatic camera image. Deep learning is compared to analytical inversion methods as well as to a compressive sensing algorithm and shows favourable characteristics both in the oversampling and in the sparse undersampling (compressive) regimes. The deep learning approach offers significant advantages in robustness to drift or noise and in reconstruction speed. In a proof-of-principle demonstrator we achieve real time recovery of hyperspectral information using a multi-core, multi-mode fiber array as a random scattering medium.
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- Current Faculties > Faculty of Engineering and Physical Sciences > School of Physics and Astronomy > Quantum, Light and Matter Group
School of Physics and Astronomy > Quantum, Light and Matter Group - Faculties (pre 2018 reorg) > Faculty of Natural and Environmental Sciences (pre 2018 reorg) > Institute for Life Sciences (pre 2018 reorg)
Current Faculties > Faculty of Environmental and Life Sciences > Institute for Life Sciences > Institute for Life Sciences (pre 2018 reorg)
Institute for Life Sciences > Institute for Life Sciences (pre 2018 reorg) - Faculties (pre 2018 reorg) > Faculty of Physical Sciences and Engineering (pre 2018 reorg) > Physics & Astronomy (pre 2018 reorg) > Quantum, Light & Matter Group (pre 2018 reorg)
Current Faculties > Faculty of Engineering and Physical Sciences > School of Physics and Astronomy > Physics & Astronomy (pre 2018 reorg) > Quantum, Light & Matter Group (pre 2018 reorg)
School of Physics and Astronomy > Physics & Astronomy (pre 2018 reorg) > Quantum, Light & Matter Group (pre 2018 reorg) - Current Faculties > Faculty of Engineering and Physical Sciences > School of Physics and Astronomy
School of Physics and Astronomy
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