An evaluation of popular hyperspectral images classification approaches

Andrey Kuznetsov; Vladislav Myasnikov

doi:10.1117/12.2228602

8 December 2015 An evaluation of popular hyperspectral images classification approaches

Andrey Kuznetsov, Vladislav Myasnikov

Proceedings Volume 9875, Eighth International Conference on Machine Vision (ICMV 2015); 987505 (2015) https://doi.org/10.1117/12.2228602
Event: Eighth International Conference on Machine Vision, 2015, Barcelona, Spain

Abstract

This work is devoted to the problem of the best hyperspectral images classification algorithm selection. The following algorithms are used for comparison: decision tree using full cross-validation; decision tree C 4.5; Bayesian classifier; maximum-likelihood method; MSE minimization classifier, including a special case – classification by conjugation; spectral angle classifier (for empirical mean and nearest neighbor), spectral mismatch classifier and support vector machine (SVM). There are used AVIRIS and SpecTIR hyperspectral images to conduct experiments.

Citation Download Citation

Andrey Kuznetsov and Vladislav Myasnikov "An evaluation of popular hyperspectral images classification approaches", Proc. SPIE 9875, Eighth International Conference on Machine Vision (ICMV 2015), 987505 (8 December 2015); https://doi.org/10.1117/12.2228602

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