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Volumn 49, Issue 1, 2006, Pages 93-101

Endmember extraction algorithms from hyperspectral images

Author keywords

Endmember extraction; Hyperspectral mixtures; Linear spectral unmixing

Indexed keywords

ALGORITHM; IMAGE; REMOTE SENSING; SENSOR;

EID: 33747198498     PISSN: 15935213     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Review
Times cited : (48)

References (16)
  • 1
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    • Endmember bundles: A new approach to incorporating endmember variability into spectral mixture analysis
    • Bateson, C.A., G.P. Asner and C.A. Wessman (2000): Endmember bundles: a new approach to incorporating endmember variability into spectral mixture analysis, IEEE Trans. Geosci. Remote Sensing, 38 (2), 1083-1094.
    • (2000) IEEE Trans. Geosci. Remote Sensing , vol.38 , Issue.2 , pp. 1083-1094
    • Bateson, C.A.1    Asner, G.P.2    Wessman, C.A.3
  • 2
    • 0002416237 scopus 로고    scopus 로고
    • Post-ATREM polishing of AVIRIS apparent reflectance data using EFFORT: A lesson in accuracy versus precision
    • Bordman, J.W (1998): Post-ATREM polishing of AVIRIS apparent reflectance data using EFFORT: a lesson in accuracy versus precision, in Proceedings of the VII NASA/JPL Airborne Earth Science Workshop.
    • (1998) Proceedings of the VII NASA/JPL Airborne Earth Science Workshop
    • Bordman, J.W.1
  • 4
    • 0002443314 scopus 로고    scopus 로고
    • Spectroscopy of rocks and minerals and principles of spectroscopy
    • in edited by A.N. Rencz (John Wiley and Sons, New York), ch. 1
    • Clark, R.N. (1999): Spectroscopy of rocks and minerals and principles of spectroscopy, in Principles of Spectroscopy, Manual of Remote Sensing, edited by A.N. Rencz (John Wiley and Sons, New York), ch. 1, 3-58.
    • (1999) Principles of Spectroscopy, Manual of Remote Sensing , pp. 3-58
    • Clark, R.N.1
  • 7
    • 0035273728 scopus 로고    scopus 로고
    • Fully constrained least squares linear mixture analysis for material quantification in hyperspectral imagery
    • Heinz, D. and C.-I. Chang (2000): Fully constrained least squares linear mixture analysis for material quantification in hyperspectral imagery, IEEE Trans. Geosci. Remote Sensing, 39, 529-545.
    • (2000) IEEE Trans. Geosci. Remote Sensing , vol.39 , pp. 529-545
    • Heinz, D.1    Chang, C.-I.2
  • 8
    • 0033099904 scopus 로고    scopus 로고
    • Multispectral and hyperspectral image analysis with convex cones
    • Ifarraguerri A. and C.-I. Chang (1999): Multispectral and hyperspectral image analysis with convex cones, IEEE Trans. Geosci. Remote Sensing, 37 (2), 756-770.
    • (1999) IEEE Trans. Geosci. Remote Sensing , vol.37 , Issue.2 , pp. 756-770
    • Ifarraguerri, A.1    Chang, C.-I.2
  • 10
    • 0004060142 scopus 로고    scopus 로고
    • Spectral-spatial analysis of remote sensing data: An image model and a procedural design
    • Ph.D. Thesis; and School of Electrical & Computer Engineering Technical Report TRECE 99-10
    • Madhok, V. and D. Landgrebe (1999): Spectral-spatial analysis of remote sensing data: an image model and a procedural design, Ph.D. Thesis; and School of Electrical & Computer Engineering Technical Report TRECE 99-10.
    • (1999)
    • Madhok, V.1    Landgrebe, D.2
  • 11
    • 0036762725 scopus 로고    scopus 로고
    • Spatial/spectral endmember extraction by multi-dimensional morphological operations
    • Plaza, A., P. Martinez, R.M. Pérez and J. Plaza (2002): Spatial/ spectral endmember extraction by multi-dimensional morphological operations, IEEE Trans. Geosci. Remote Sensing, 40 (9), 2025-2041.
    • (2002) IEEE Trans. Geosci. Remote Sensing , vol.40 , Issue.9 , pp. 2025-2041
    • Plaza, A.1    Martinez, P.2    Pérez, R.M.3    Plaza, J.4
  • 16
    • 0033310314 scopus 로고    scopus 로고
    • N-FINDR: An algorithm for fast autonomous spectral end-member determination in hyperspectral data
    • Winter, M.E. (1999): N-FINDR: an algorithm for fast autonomous spectral end-member determination in hyperspectral data, SPIE Proc., 3753, 266-275.
    • (1999) SPIE Proc. , vol.3753 , pp. 266-275
    • Winter, M.E.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.