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Deep Optimal Filter Responses for Multi-Spectral Imaging
  DOI :  10.2352/issn.2694-118X.2020.LIM-14  Published OnlineSeptember 2020
Abstract

Spectral recovery from measured camera signals based on deep learning lead to significant advancements of the potential reconstruction quality. However, most deep learning based approaches only consider RGB cameras and are targeting object classification in particular or remote sensing in general as their final application. Within this work, we analyze the influence of a joint filter optimization and spectral recovery for multi-spectral image acquisition with the underlying goal of capturing high-fidelity color images. An evaluation on the influence of the total camera channel count on the reproduction quality is provided. Finally, a possible normalization of spectral data is discussed.

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Tarek Stiebel, Dorit Merhof, "Deep Optimal Filter Responses for Multi-Spectral Imagingin Proc. IS&T London Imaging Meeting 2020: Future Colour Imaging,  2020,  pp 134 - 138,  https://doi.org/10.2352/issn.2694-118X.2020.LIM-14

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Copyright © Society for Imaging Science and Technology 2020
75011771
London Imaging Meeting
2694-118X
2694-118x
Society for Imaging Science and Technology