Artículos de revistas
Toward Satellite-based Land Cover Classification Through Optimum-path Forest
Registro en:
Ieee Transactions On Geoscience And Remote Sensing. Institute Of Electrical And Electronics Engineers Inc., v. 52, n. 10, p. 6075 - 6085, 2014.
1962892
10.1109/TGRS.2013.2294762
2-s2.0-84902077626
Autor
Pisani R.J.
Nakamura R.Y.M.
Riedel P.S.
Zimback C.R.L.
Falcao A.X.
Papa J.P.
Institución
Resumen
Land cover classification has been paramount in the last years. Since the amount of information acquired by satellite on-board imaging systems has increased, there is a need for automatic tools that can tackle such problem. Despite the fact that one can find several works in the literature, we propose a novel methodology for land cover classification by means of the optimum-path forest (OPF) framework, which has never been applied to this context up to date. Experiments were conducted in supervised and unsupervised situations against some state-of-the-art pattern recognition techniques, such as support vector machines, Bayesian classifier, k-means, and mean shift. We had shown that supervised OPF can outperform such approaches, being much faster than all. 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