Hyperspectral image analysis for precision viticulture

Authors:
M. Ferreiro-Armán;J. -P. Da Costa;S. Homayouni;J. Martín-Herrero
Affiliations:
Departamento de Teoría do Sinal e Comunicacións, ETSET, Universidade de Vigo, Spain;LAPS – UMR 5131 CNRS, Université Bordeaux 1, Talence, France;LAPS – UMR 5131 CNRS, Université Bordeaux 1, Talence, France;Departamento de Teoría do Sinal e Comunicacións, ETSET, Universidade de Vigo, Spain
Venue:
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part II
Year:
2006

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Abstract

We analyze the capabilities of CASI data for the discrimination of vine varieties in hyperspectral images. To analyze the discrimination capabilities of the CASI data, principal components analysis and linear discriminant analysis methods are used. We assess the performance of various classification techniques: Multi-layer perceptrons, radial basis function neural networks, and support vector machines. We also discuss the trade-off between spatial and spectral resolutions in the framework of precision viticulture.