Manifold-learning-based feature extraction for classification of hyperspectral data: A review of advances in manifold learning

IEEE Signal Processing Magazine

Volumn 31, Issue 1, 2014, Pages 55-66

  Lunga, Dalton ^a   Prasad, Saurabh ^b   Crawford, Melba M ^c   Ersoy, Okan ^d  

^a CSIR MERAKA INSTITUTE   (South Africa)

^b University of Houston   (United States)

^c PURDUE UNIVERSITY   (United States)

^d Purdue University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; DATA VISUALIZATION; EXTRACTION; FEATURE EXTRACTION; PIXELS; RANDOM PROCESSES; SPECTRAL RESOLUTION; SPECTROSCOPY; STOCHASTIC SYSTEMS;

DIMENSIONALITY REDUCTION; FEATURE SELECTION AND EXTRACTIONS; HIGH SPECTRAL RESOLUTION; HYPER-SPECTRAL IMAGERIES; MULTIPATH SCATTERING; NONLINEAR CHARACTERISTICS; OPTIMAL FEATURE SELECTIONS; SPECTRAL INFORMATION;

CLASSIFICATION (OF INFORMATION);

EID: 85032751123     PISSN: 10535888     EISSN: None     Source Type: Journal    
DOI: 10.1109/MSP.2013.2279894     Document Type: Article

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