Hyperspectral anomaly detection based on minimum generalized variance method

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 6966, Issue , 2008, Pages

  Lo, Edisanter ^a   John Ingram, L T C ^b  

^a SUSQUEHANNA UNIVERSITY   (United States)

^b UNITED STATES MILITARY ACADEMY   (United States)

Author keywords

Anomaly detection; Hyperspectral imaging; Robust statistics

Indexed keywords

ANOMALY DETECTIONS; GENERALIZED VARIANCE; HYPER-SPECTRAL; HYPERSPECTRAL ANOMALY DETECTION; HYPERSPECTRAL IMAGE (HSI); MAHALANOBIS DISTANCE (MD); MULTI-SPECTRAL (MS); NUMERICA L RESULTS; ROBUST STATISTICS; SAMPLE STATISTICS; ULTRASPECTRAL;

ADMINISTRATIVE DATA PROCESSING; ALGORITHMS; ATMOSPHERICS; CLASSIFICATION (OF INFORMATION); ESTIMATION; EVOLUTIONARY ALGORITHMS; FIBER OPTIC SENSORS; FINANCIAL DATA PROCESSING; IMAGING TECHNIQUES; NUMERICAL METHODS; PARAMETER ESTIMATION; PIXELS; STATISTICAL METHODS; STATISTICS; TECHNOLOGY;

POPULATION STATISTICS;

EID: 44949088729     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.778929     Document Type: Conference Paper

References (5)

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