Cluster versus GPU implementation of an orthogonal target detection algorithm for remotely sensed hyperspectral images

Proceedings - IEEE International Conference on Cluster Computing, ICCC

Volumn , Issue , 2010, Pages 227-234

  Paz, Abel ^a   Plaza, Antonio ^a  

^a UNIVERSITY OF EXTREMADURA   (Spain)

Author keywords

Clusters of computers; Graphics processing units (GPUs); Hyperspectral data; Target detection

Indexed keywords

AIRBORNE VISIBLE INFRARED IMAGING SPECTROMETER; ANOMALY DETECTION; CLUSTER-BASED IMPLEMENTATIONS; CLUSTERS OF COMPUTERS; COMPUTING PERFORMANCE; DETECTING OBJECTS; GODDARD SPACE FLIGHT CENTER; GPU IMPLEMENTATION; GRAPHICS PROCESSING UNIT; GRAPHICS PROCESSING UNITS; HIGH DIMENSIONAL DATA; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL; HYPERSPECTRAL DATA; HYPERSPECTRAL IMAGING; INFORMATION EXTRACTION; MARYLAND; NEW YORK; ORTHOGONAL SUBSPACE PROJECTION; PARALLEL CLUSTERS; PARALLEL COMPUTING ARCHITECTURE; PARALLEL IMPLEMENTATIONS; PARALLEL VERSION; REAL TIME; REMOTE SENSING DATA; SPECTRAL DOMAINS; SURVEILLANCE APPLICATIONS; TARGET DETECTION; TARGET DETECTION ALGORITHM; WORLD TRADE CENTER;

CLUSTER COMPUTING; CLUSTERING ALGORITHMS; COMPUTER GRAPHICS EQUIPMENT; IMAGE CODING; INFRARED IMAGING; INTERNATIONAL TRADE; OFFICE BUILDINGS; PARALLEL ALGORITHMS; PARALLEL ARCHITECTURES; PROGRAM PROCESSORS; REMOTE SENSING; SIGNAL DETECTION; SPACE FLIGHT; TARGET DRONES; TARGET TRACKING;

RADAR TARGET RECOGNITION;

EID: 78649482165     PISSN: 15525244     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CLUSTER.2010.28     Document Type: Conference Paper

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