Geometrie estimation of the inherent dimensionality of a single material cluster in multi- and hyperspectral imagery

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 6966, Issue , 2008, Pages

  Schlamm, Ariel ^a   Messinger, David ^a   Basener, William ^a  

^a ROCHESTER INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Hyperspace; Hyperspectral; Inherent dimension

Indexed keywords

ALGORITHMS; ESTIMATION; EVOLUTIONARY ALGORITHMS; FIBER OPTIC SENSORS; FUNCTION EVALUATION; NUMBER THEORY; NUMERICAL METHODS; PIGMENTS; PRINCIPAL COMPONENT ANALYSIS; SET THEORY; TECHNOLOGY; VECTORS;

(2+1) DIMENSIONS; (2+1)-DIMENSIONAL; (SPM) CLASSES; APPLIED (CO); COMPLEX SCENES; DATA POINTS; DATA SETS; EIGENVALUES (OF GRAPHS); GEOMETRIC APPROACHES; HYPER-SPECTRAL; HYPERSPECTRAL IMAGERY (HSI); INDIVIDUAL COMPONENTS; LOCAL ESTIMATION; MINIMUM NOISE FRACTION (MNF); MULTI-SPECTRAL (MS); NATURAL MATERIALS; POINT DENSITY; PRINCIPAL COMPONENTS ANALYSIS (PCA); SPECTRAL CHANNELS; STATISTICAL MEASURES; ULTRASPECTRAL; VIRTUAL DIMENSIONALITY (VD);

MATHEMATICAL TRANSFORMATIONS;

EID: 44949178576     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.776903     Document Type: Conference Paper

References (6)

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