Nature-Inspired Framework for Hyperspectral Band Selection
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Institute of Electrical and Electronics Engineers (IEEE)
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Resumo
Although 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.
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Evolutionary computation, heuristic algorithms, hyperspectral imaging, image classification, pattern recognition
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Inglês
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Ieee Transactions On Geoscience And Remote Sensing. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 52, n. 4, p. 2126-2137, 2014.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
AMD
Microsoft
