Novel two-dimensional singular spectrum analysis for effective feature extraction and data classification in hyperspectral imaging

IEEE Transactions on Geoscience and Remote Sensing

Volumn 53, Issue 8, 2015, Pages 4418-4433

  Zabalza, Jaime ^a   Ren, Jinchang ^a   Zheng, Jiangbin ^b   Han, Junwei ^b   Zhao, Huimin ^c   Li, Shutao ^d   Marshall, Stephen ^a  

^a UNIVERSITY OF STRATHCLYDE   (United Kingdom)

^b NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

^c GUANGDONG POLYTECHNIC NORMAL UNIVERSITY   (China)

^d HUNAN UNIVERSITY   (China)

Author keywords

2 D empirical mode decomposition (2D EMD); 2 D singular spectrum analysis (2D SSA); Data classification; feature extraction; hyperspectral imaging (HSI)

Indexed keywords

DATA MINING; FEATURE EXTRACTION; IMAGE PROCESSING; NEAREST NEIGHBOR SEARCH; PRINCIPAL COMPONENT ANALYSIS; REMOTE SENSING; SIGNAL PROCESSING; SPECTROSCOPY; SPECTRUM ANALYSIS;

DATA CLASSIFICATION; EMPIRICAL MODE DECOMPOSITION; HYPERSPECTRAL IMAGING; REMOTE-SENSING DATA CLASSIFICATION; SINGULAR SPECTRUM ANALYSIS; SPATIAL INFORMATION EXTRACTION; SPECTRAL FEATURE EXTRACTION; SUPPORT VECTOR MACHINE CLASSIFIERS;

CLASSIFICATION (OF INFORMATION);

BENCHMARKING; DATA ASSIMILATION; DATA SET; EMPIRICAL ANALYSIS; EXPERIMENTAL STUDY; EXTRACTION METHOD; NEAREST NEIGHBOR ANALYSIS; PRINCIPAL COMPONENT ANALYSIS; QUANTITATIVE ANALYSIS; REMOTE SENSING; SPECTRAL ANALYSIS; TWO-DIMENSIONAL MODELING; VECTOR;

EID: 85027941688     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2015.2398468     Document Type: Article

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