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Volumn , Issue , 2009, Pages

Hyperspectral image classification based on spectral and geometrical features

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION RESULTS; CONTEXTUAL FEATURE; FEATURE DIMENSIONS; GEOMETRICAL FEATURES; HYPER-SPECTRAL IMAGES; HYPERSPECTRAL IMAGE CLASSIFICATION; LINEAR UNMIXING; LOCAL SCALE; MORPHOLOGICAL PROFILE; SPECTRAL FEATURE; SPECTRAL INFORMATION; TOPOGRAPHIC MAP;

EID: 77950952599     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MLSP.2009.5306266     Document Type: Conference Paper
Times cited : (16)

References (13)
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  • 2
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  • 5
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    • Kernel principal component analysis for the classification of hyperspectral remote-sensing data over urban areas
    • to appear
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  • 7
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  • 8
    • 24944572607 scopus 로고    scopus 로고
    • Supervised segmentation of remote sensing images based on a tree-structured MRF model
    • DOI 10.1109/TGRS.2005.852163
    • G. Poggi, G. Scarpa, and J. Zerubia, "Supervised segmentation of remote sensing images based on a tree-structure MRF model," IEEE Trans. on Geoscience and Remote Sensing, vol.43, no.8, pp. 1901-1911, 2005. (Pubitemid 41329037)
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  • 9
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    • Febrary
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  • 11
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    • Camps-Valls, G.1    Bruzzone, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.