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Volumn 2003-January, Issue , 2004, Pages 93-98

Band selection using independent component analysis for hyperspectral image processing

Author keywords

[No Author keywords available]

Indexed keywords

DATA FUSION; FEATURE EXTRACTION; IMAGE ANALYSIS; IMAGE PROCESSING; INDEPENDENT COMPONENT ANALYSIS; PATTERN RECOGNITION; SPECTROSCOPY;

EID: 84923058832     PISSN: 21642516     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/AIPR.2003.1284255     Document Type: Conference Paper
Times cited : (115)

References (21)
  • 1
    • 84898956124 scopus 로고    scopus 로고
    • Viewpoint invariant face recognition using independent component analysis and attractor networks
    • chapter MIT Press, Cambridge, MA
    • M. S. Bartlett and T. J. Sejnowski. Viewpoint invariant face recognition using independent component analysis and attractor networks, chapter Neural Information Processing Systems-Natural and Synthetic 9, pages 817-823. MIT Press, Cambridge, MA, 1997.
    • (1997) Neural Information Processing Systems-Natural and Synthetic , vol.9 , pp. 817-823
    • Bartlett, M.S.1    Sejnowski, T.J.2
  • 2
    • 0036821665 scopus 로고    scopus 로고
    • Dimensionality reduction of hyperspectral data using discrete wavelet transform feature extraction
    • October
    • L. Bruce, C. Koger, and J. Li. Dimensionality reduction of hyperspectral data using discrete wavelet transform feature extraction. IEEE Transactions on Geoscience and Remote Sensing, 40(10):2331-2338, October 2002.
    • (2002) IEEE Transactions on Geoscience and Remote Sensing , vol.40 , Issue.10 , pp. 2331-2338
    • Bruce, L.1    Koger, C.2    Li, J.3
  • 3
    • 0033341402 scopus 로고    scopus 로고
    • A noise subspace projection approach to determination of intrinsic dimensionality for hyperspectral imagery
    • Florence, Italy, Sep 20-24
    • C.-I. Chang and Q. Du. A noise subspace projection approach to determination of intrinsic dimensionality for hyperspectral imagery. In EOS/SPIE Symosium on Remote Sensing, Conference on Image and Signal Processing for Remote Sensing V., volume 3871, pages 34-44, Florence, Italy, Sep 20-24 1999.
    • (1999) EOS/SPIE Symosium on Remote Sensing, Conference on Image and Signal Processing for Remote Sensing V , vol.3871 , pp. 34-44
    • Chang, C.-I.1    Du, Q.2
  • 4
    • 0033224770 scopus 로고    scopus 로고
    • A joint band prioritization and band-decorrelation approach to band selection for hyperspectral image classification
    • November
    • C.-I. Chang, Q. Du, T.-L. Sun, and M. Althouse. A joint band prioritization and band-decorrelation approach to band selection for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, 37(6):2631-2641, November 1999.
    • (1999) IEEE Transactions on Geoscience and Remote Sensing , vol.37 , Issue.6 , pp. 2631-2641
    • Chang, C.-I.1    Du, Q.2    Sun, T.-L.3    Althouse, M.4
  • 5
    • 0034543937 scopus 로고    scopus 로고
    • Unsupervised hyperspectral image analysis using independent component analysis
    • Honolulu, HI, USA, 24-28 July IEEE
    • S. Chiang, C. Chang, and I. W. Ginsberg. Unsupervised hyperspectral image analysis using independent component analysis. In Geoscience and Remote Sensing Symposium, Proc. IGARSS 2000, volume 4, pages 3136-3138, Honolulu, HI, USA, 24-28 July 2000. IEEE.
    • (2000) Geoscience and Remote Sensing Symposium, Proc. IGARSS 2000 , vol.4 , pp. 3136-3138
    • Chiang, S.1    Chang, C.2    Ginsberg, I.W.3
  • 6
    • 0028416938 scopus 로고
    • Independent component analysis, a new concept?
    • April Special Issue on High-order Statistics
    • P. Common. Independent component analysis, a new concept? Signal Processing, 36(3):287-314, April 1994. Special Issue on High-order Statistics.
    • (1994) Signal Processing , vol.36 , Issue.3 , pp. 287-314
    • Common, P.1
  • 9
    • 0346307721 scopus 로고    scopus 로고
    • A fast fixed-point algorithm for independent component analysis
    • A. Hyvärinen and E. Oja. A fast fixed-point algorithm for independent component analysis. Neural Computation, 9:1483-1492, 1997.
    • (1997) Neural Computation , vol.9 , pp. 1483-1492
    • Hyvärinen, A.1    Oja, E.2
  • 10
    • 0042826822 scopus 로고    scopus 로고
    • Independent component analysis: Algorithms and applications
    • A. Hyvärunen and E. Oja. Independent component analysis: Algorithms and applications. Neural Networks, 13(4-5):411-430, 2000.
    • (2000) Neural Networks , vol.13 , Issue.4-5 , pp. 411-430
    • Hyvärunen, A.1    Oja, E.2
  • 12
    • 85032751896 scopus 로고    scopus 로고
    • Hyperspectral image data analysis as a high dimensional signal processing problem
    • January
    • D. Landgrebe. Hyperspectral image data analysis as a high dimensional signal processing problem. Special Issue of the IEEE Signal Processing Magazine, 19(1):17-28, January 2002.
    • (2002) Special Issue of the IEEE Signal Processing Magazine , vol.19 , Issue.1 , pp. 17-28
    • Landgrebe, D.1
  • 13
    • 3543109539 scopus 로고    scopus 로고
    • Independent component analysis as a tool for the dimensionality reduction and the representation of hyperspectral images
    • Toulouse, France, Sept 19-21
    • M. Lennon, G. Mercier, M. C. Mouchot, and L. Hubert-Moy. Independent component analysis as a tool for the dimensionality reduction and the representation of hyperspectral images. In SPIE Remote Sensing, volume 4541, pages 2893-2895, Toulouse, France, Sept 19-21 2001.
    • (2001) SPIE Remote Sensing , vol.4541 , pp. 2893-2895
    • Lennon, M.1    Mercier, G.2    Mouchot, M.C.3    Hubert-Moy, L.4
  • 14
    • 0031997059 scopus 로고    scopus 로고
    • Supervised classification in high dimensional space: Geometrical, statistical, and asymptotical properties of multivariate data
    • February
    • J. Luis and D. Landgrebe. Supervised classification in high dimensional space: Geometrical, statistical, and asymptotical properties of multivariate data. IEEE Trans. on System, Man, and Cybernetics, 28, Part C(1):39-54, February 1998.
    • (1998) IEEE Trans. on System, Man, and Cybernetics , vol.28 , Issue.1 , pp. 39-54
    • Luis, J.1    Landgrebe, D.2
  • 18
    • 0015744443 scopus 로고
    • Two effective feature selection criteria for multispectral remote sensing
    • Washington, DC, November LARS Technical Note 042673
    • P. Swain and R. King. Two effective feature selection criteria for multispectral remote sensing. In International Joint Conference On Pattern Recognition, Washington, DC, November 1973. LARS Technical Note 042673.
    • (1973) International Joint Conference on Pattern Recognition
    • Swain, P.1    King, R.2
  • 19
    • 0035691645 scopus 로고    scopus 로고
    • Nonlinear blind source separation using higher order statistics and a genetic algorithm
    • Y. Tan and J. Wang. Nonlinear blind source separation using higher order statistics and a genetic algorithm. IEEE Transactions on Evolutionary Computation, 5(6):600-612, 2001.
    • (2001) IEEE Transactions on Evolutionary Computation , vol.5 , Issue.6 , pp. 600-612
    • Tan, Y.1    Wang, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.