Nature-inspired framework for hyperspectral band selection

IEEE Transactions on Geoscience and Remote Sensing

Volumn 52, Issue 4, 2014, Pages 2126-2137

  Nakamura, Rodrigo Y M ^a   Fonseca, Leila Maria Garcia ^b   Santos, Jefersson Alex Dos ^c   Torres, Ricardo Da S ^c   Yang, Xin She ^d   Papa, Joao Papa ^a  

^a SÃO PAULO STATE UNIVERSITY UNESP   (Brazil)

^b INSTITUTO NACIONAL DE PESQUISAS ESPACIAIS   (Brazil)

^c UNIVERSITY OF CAMPINAS   (Brazil)

^d MIDDLESEX UNIVERSITY   (United Kingdom)

Author keywords

Evolutionary computation; heuristic algorithms; hyperspectral imaging; image classification; pattern recognition

Indexed keywords

EVOLUTIONARY ALGORITHMS; HEURISTIC ALGORITHMS; IMAGE CLASSIFICATION; PATTERN RECOGNITION;

BAND SELECTION; COMPUTATION COSTS; HIGHLY-CORRELATED; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL IMAGING; LARGE AMOUNTS OF DATA; META HEURISTIC ALGORITHM; OPTIMUM-PATH FORESTS;

SPECTROSCOPY;

COMPUTER SIMULATION; CORRELATION; DATA SET; IMAGE ANALYSIS; IMAGE CLASSIFICATION; OPTIMIZATION; PATTERN RECOGNITION; SATELLITE IMAGERY; SPECTRAL ANALYSIS; WAVELENGTH;

EID: 84892590567     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2013.2258351     Document Type: Article

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