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Volumn 3, Issue , 2004, Pages 1601-1604

A hybrid algorithm for subpixel detection in hyperspectral imagery

Author keywords

Hyperspectral; Spectral unmixing; Subpixel detection

Indexed keywords

ALGORITHMS; ARRAYS; DEMODULATION; ERROR ANALYSIS; LEAST SQUARES APPROXIMATIONS; MATHEMATICAL MODELS; REFLECTION; SPECTROSCOPY; SPECTRUM ANALYSIS;

EID: 15944387338     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (23)

References (8)
  • 2
    • 0028467206 scopus 로고
    • Hyperspectral image classification and dimensionality reduction: An orthogonal subspace projection approach
    • July
    • J.C. Harsanyi, C-I Chang, "Hyperspectral Image Classification and Dimensionality Reduction: An Orthogonal Subspace Projection Approach," IEEE TGRS, Vol. 32, No. 4, July 1994.
    • (1994) IEEE TGRS , vol.32 , Issue.4
    • Harsanyi, J.C.1    Chang, C.-I.2
  • 3
    • 0033719885 scopus 로고    scopus 로고
    • Constrained subpixel target detection for remotely sensed imagery
    • May
    • C-I Chang, D.C. Heinz. "Constrained Subpixel Target Detection for Remotely Sensed Imagery," IEEE TGRS, Vol. 38, No. 3, May 2000.
    • (2000) IEEE TGRS , vol.38 , Issue.3
    • Chang, C.-I.1    Heinz, D.C.2
  • 4
    • 0035273728 scopus 로고    scopus 로고
    • Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery
    • March
    • D.C. Heinz. C-I Chang. "Fully Constrained Least Squares Linear Spectral Mixture Analysis Method for Material Quantification in Hyperspectral Imagery."'IEEE TGRS, Vol. 39, No. 3, March 2001.
    • (2001) IEEE TGRS , vol.39 , Issue.3
    • Heinz, D.C.1    Chang, C.-I.2
  • 5
    • 0032658498 scopus 로고    scopus 로고
    • The CFAR adaptive sub-space detector is a scale-invariant GLRT
    • Sept.
    • S. Kraut, L. Sharf, "The CFAR adaptive sub-space detector is a scale-invariant GLRT," IEEE Trans. Signal Processing, Vol. 47, Sept. 1999.
    • (1999) IEEE Trans. Signal Processing , vol.47
    • Kraut, S.1    Sharf, L.2
  • 6
    • 0035392132 scopus 로고    scopus 로고
    • Hyperspectral subpixel target detection using the linear mixing model
    • July
    • D. Manolakis, C. Siracusa, G. Shaw, "Hyperspectral Subpixel Target Detection Using the Linear Mixing Model." IEEE TGRS, Vol. 39, No. 7, July 2001.
    • (2001) IEEE TGRS , vol.39 , Issue.7
    • Manolakis, D.1    Siracusa, C.2    Shaw, G.3
  • 7
    • 0019584940 scopus 로고
    • An algorithm for linear least squares problems with equality and non-negativity constraints generalized
    • K.H. Haskell and R.J. Hansen. "An algorithm for linear least squares problems with equality and non-negativity constraints generalized." Math Prog., Vol. 21, 1981.
    • (1981) Math Prog. , vol.21
    • Haskell, K.H.1    Hansen, R.J.2
  • 8
    • 0000385570 scopus 로고    scopus 로고
    • Fast autonomous spectral endmember determination in hyperspectral data
    • Vancouver, BC, Canada
    • M.E. Winter, "Fast autonomous spectral endmember determination in hyperspectral data." in Proc. 13th Int. Conf. Applied Geologic Remote Sensing, vol. II, Vancouver, BC, Canada, 1999, pp. 337-344.
    • (1999) Proc. 13th Int. Conf. Applied Geologic Remote Sensing , vol.2 , pp. 337-344
    • Winter, M.E.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.