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Volumn 47, Issue 28, 2008, Pages

End-member extraction for hyperspectral image analysis

Author keywords

[No Author keywords available]

Indexed keywords

SPECTROSCOPY;

EID: 60749110419     PISSN: 1559128X     EISSN: 15394522     Source Type: Journal    
DOI: 10.1364/AO.47.000F77     Document Type: Article
Times cited : (91)

References (9)
  • 1
    • 0033310314 scopus 로고    scopus 로고
    • N-FINDR: An algorithm for fast autonomous spectral end-member determination in hyperspectral data
    • M. E. Winter, "N-FINDR: an algorithm for fast autonomous spectral end-member determination in hyperspectral data," Proc, SPIE 3753, 266-275 (1999).
    • (1999) Proc, SPIE , vol.3753 , pp. 266-275
    • Winter, M.E.1
  • 2
    • 1642290713 scopus 로고    scopus 로고
    • Automatic spectral target recognition in hyperspectral imagery
    • H. Ren and C.-I. Chang, "Automatic spectral target recognition in hyperspectral imagery," IEEE Trans. Aerosp. Electron. Syst. 39, 1232-1249 (2003).
    • (2003) IEEE Trans. Aerosp. Electron. Syst , vol.39 , pp. 1232-1249
    • Ren, H.1    Chang, C.-I.2
  • 3
    • 0028467206 scopus 로고
    • Hyperspectral image classification and dimensionality reduction: An orthogonal subspace projection
    • J. C. Harsanyi and C.-I. Chang, "Hyperspectral image classification and dimensionality reduction: an orthogonal subspace projection," IEEE Trans. Geosci. Remote Sens. 32, 779-785 (1994).
    • (1994) IEEE Trans. Geosci. Remote Sens , vol.32 , pp. 779-785
    • Harsanyi, J.C.1    Chang, C.-I.2
  • 4
    • 16444373735 scopus 로고    scopus 로고
    • Vertex component analysis: A fast algorithm to unmix hyperspectral data
    • J. M. P. Nascimento and J. M. Bioucas Dias, "Vertex component analysis: a fast algorithm to unmix hyperspectral data," IEEE Trans. Geosci. Remote Sens. 43, 898-910 (2005).
    • (2005) IEEE Trans. Geosci. Remote Sens , vol.43 , pp. 898-910
    • Nascimento, J.M.P.1    Bioucas Dias, J.M.2
  • 5
    • 0035273728 scopus 로고    scopus 로고
    • Fully constrained least squares linear mixture analysis for material quantification in hyperspectral imagery
    • D. Heinz and C.-I. Chang, "Fully constrained least squares linear mixture analysis for material quantification in hyperspectral imagery," IEEE Trans. Geosci. Remote Sens. 39, 529-545 (2001).
    • (2001) IEEE Trans. Geosci. Remote Sens , vol.39 , pp. 529-545
    • Heinz, D.1    Chang, C.-I.2
  • 7
    • 0028545567 scopus 로고
    • A faster way to compute the noise-adjusted principal components transform matrix
    • R. E. Roger, "A faster way to compute the noise-adjusted principal components transform matrix," IEEE Trans. Geosci. Remote Sens. 32, 1194-1196 (1994).
    • (1994) IEEE Trans. Geosci. Remote Sens , vol.32 , pp. 1194-1196
    • Roger, R.E.1
  • 9
    • 33845599430 scopus 로고    scopus 로고
    • Iterative spectral unmixing for optimizing per-pixel endmembers sets
    • D. M. Rogge, B. Rivard, J. Zhang, and J. Feng, "Iterative spectral unmixing for optimizing per-pixel endmembers sets," IEEE Trans. Geosci. Remote Sens. 44, 3725-3736 (2006).
    • (2006) IEEE Trans. Geosci. Remote Sens , vol.44 , pp. 3725-3736
    • Rogge, D.M.1    Rivard, B.2    Zhang, J.3    Feng, J.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.