Feature selection for classification of remote sensed hyperspectral images: A filter approach using genetic algorithm and cluster validity

Proceedings of the 2012 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2012

Volumn 2, Issue , 2012, Pages 675-681

  Santos, A B ^a   Celes, C S F D S ^a   Araujo A D A ^a   Menotti, D ^b  

^a FEDERAL UNIVERSITY OF MINAS GERAIS   (Brazil)

^b FEDERAL UNIVERSITY OF OURO PRETO   (Brazil)

Author keywords

Cluster validity; Filter feature selection; Genetic algorithm; Hyperspectral image; Pattern classification

Indexed keywords

CLASSIFICATION METHODS; CLUSTER VALIDITY; CLUSTER VALIDITY MEASURES; DATA SETS; DECISION BOUNDARY; FILTER APPROACH; HYPER-SPECTRAL IMAGES; INTRA-CLUSTER; K-NEAREST NEIGHBORS; MULTILAYER PERCEPTION NEURAL NETWORKS; SUBSET SELECTION;

COMPUTER VISION; EXPERIMENTS; GENETIC ALGORITHMS; INDEPENDENT COMPONENT ANALYSIS; OPTIMIZATION; PATTERN RECOGNITION; REMOTE SENSING; SPECTROSCOPY; SUPPORT VECTOR MACHINES;

SET THEORY;

EID: 84873316248     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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