Nakamura, Rodrigo Y. M. [UNESP]Garcia Fonseca, Leila MariaSantos, Jefersson Alex dosTorres, Ricardo da S.Yang, Xin-ShePapa, João Paulo [UNESP]2014-12-032014-12-032014-04-01Ieee Transactions On Geoscience And Remote Sensing. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 52, n. 4, p. 2126-2137, 2014.0196-2892http://hdl.handle.net/11449/113507Although hyperspectral images acquired by on-board satellites provide information from a wide range of wavelengths in the spectrum, the obtained information is usually highly correlated. This paper proposes a novel framework to reduce the computation cost for large amounts of data based on the efficiency of the optimum-path forest (OPF) classifier and the power of metaheuristic algorithms to solve combinatorial optimizations. Simulations on two public data sets have shown that the proposed framework can indeed improve the effectiveness of the OPF and considerably reduce data storage costs.2126-2137engEvolutionary computationheuristic algorithmshyperspectral imagingimage classificationpattern recognitionArtigo10.1109/TGRS.2013.2258351WOS:000329527000018Acesso restrito9039182932747194