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On the value of the Kullback–Leibler divergence for cost-effective spectral imaging of plants by optimal selection of wavebands

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Abstract

The practical value of a criterion based on statistical information theory is demonstrated for the selection of optimal wavelength and bandwidth of low-cost lighting systems in plant imaging applications. Kullback–Leibler divergence is applied to the problem of spectral band reduction from hyperspectral imaging. The results are illustrated on various plant imaging problems and show similar results to the one obtained with state-of-the-art criteria. A specific interest of the proposed approach is to offer the possibility to integrate technological constraints in the optimization of the spectral bands selected.

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Acknowledgments

This work received support from the French Government supervised by the Agence Nationale de la Recherche in the framework of the program Investissements d’Avenir under reference ANR-11-BTBR-0007 (AKER program). Landry BENOIT gratefully acknowledges financial support from Angers Loire Metropole and GEVES-SNES for the preparation of his PhD.

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Authors and Affiliations

  1. Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), Université d’Angers, 62 avenue Notre Dame du Lac, 49000, Angers, France

    Landry Benoit, Romain Benoit, Étienne Belin & François Chapeau-Blondeau

  2. GEVES, Station Nationale d’Essais de Semences (SNES), 25 rue Georges Morel, 49071, Beaucouzé, France

    Rodolphe Vadaine & Didier Demilly

  3. CREATIS; CNRS UMR 5220; INSERM U1044; Université Lyon 1, INSA-Lyon, Université de Lyon, 69621, Villeurbanne, France

    David Rousseau

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  1. Landry Benoit
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  2. Romain Benoit
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  3. Étienne Belin
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  4. Rodolphe Vadaine
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  5. Didier Demilly
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  6. François Chapeau-Blondeau
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  7. David Rousseau
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Correspondence to David Rousseau.

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Benoit, L., Benoit, R., Belin, É. et al. On the value of the Kullback–Leibler divergence for cost-effective spectral imaging of plants by optimal selection of wavebands. Machine Vision and Applications 27, 625–635 (2016). https://doi.org/10.1007/s00138-015-0717-7

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  • DOI: https://doi.org/10.1007/s00138-015-0717-7

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