Including the spatial context into decision fusion for urban area mapping using hyperspectral data

International Geoscience and Remote Sensing Symposium (IGARSS)

Volumn , Issue , 2012, Pages 1590-1593

  Lisini, G ^a   Gamba, P ^b   Bakos, K L ^c,d  

^a SCUOLA UNIVERSITARIA SUPERIORE IUSS PAVIA   (Italy)

^b UNIVERSITY OF PAVIA   (Italy)

^c UNIVERSITY OF DEBRECEN   (Hungary)

^d UNIVERSITY OF WARSAW   (Poland)

Author keywords

hyperspectral; segmentation; spectral spatial classification; urban classification

Indexed keywords

BINARY DECISION TREES; CANNY EDGE DETECTORS; CLASS PROBABILITIES; CLASSIFICATION RESULTS; CLASSIFICATION STRUCTURE; DECISION FUSION; ENSEMBLE CLASSIFICATION; GENERIC MAPPING; HYPERSPECTRAL; HYPERSPECTRAL DATA; IMAGE OBJECTS; MEMBERSHIP VALUES; NOVEL METHODOLOGY; REGION GROWING; SPATIAL ALGORITHMS; SPATIAL CONTEXT; SPATIAL DOMAINS; SPATIAL EXTENSION; SPATIAL INFORMATIONS; SPECTRAL DOMAINS; SPECTRAL-SPATIAL CLASSIFICATION; URBAN AREAS; URBAN CLASSIFICATION; URBAN ENVIRONMENTS;

BINARY TREES; DECISION TREES; GEOLOGY; IMAGE SEGMENTATION; OPTIMIZATION; REMOTE SENSING; URBAN PLANNING;

PHOTOMAPPING;

EID: 84873120611     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2012.6350813     Document Type: Conference Paper

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