Support vector machines for broad area feature classification in remotely sensed images

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 4381, Issue 1, 2001, Pages 286-295

  Perkins, Simon ^a   Harvey, Neal R ^a   Brumby, Steven P ^a   Lacker, Kevin ^a  

^a LOS ALAMOS NATIONAL LABORATORY   (United States)

Author keywords

Feature construction; Hyperspectral imagery; Image feature classification; Multispectral imagery; Remote sensing; Spatial context; Supervised learning; Support vector machines

Indexed keywords

IMAGE ANALYSIS; LEARNING SYSTEMS; PROBABILITY; SATELLITE COMMUNICATION SYSTEMS; SPECTRUM ANALYSIS; VECTOR QUANTIZATION;

BROAD AREA FEATURE CLASSIFICATION; MULTISPECTRAL IMAGERY; SUPPORT VECTOR MACHINES (SVM);

REMOTE SENSING;

EID: 0035172225     PISSN: 0277786X     EISSN: None     Source Type: Journal    
DOI: 10.1117/12.437019     Document Type: Article

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