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Article Dans Une Revue Machine Vision and Applications Année : 2016

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

Résumé

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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Dates et versions

hal-01392039 , version 1 (04-11-2016)

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Landry Benoit, Romain Benoit, Etienne Belin, Rodolphe Vadaine, Didier Demilly, 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, 2016, 27, pp.625-635. ⟨10.1007/s00138-015-0717-7⟩. ⟨hal-01392039⟩
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