메뉴 건너뛰기




Volumn , Issue , 2006, Pages 149-177

Unmixing Hyperspectral Data: Independent and Dependent Component Analysis

Author keywords

Hyperspectral abundance fraction dependence impact on ICA IFA algorithms; Independent component analysis (ICA) and independent factor analysis (IFA); Unmixing hyperspectral data

Indexed keywords


EID: 77953610841     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9780470124628.ch6     Document Type: Chapter
Times cited : (6)

References (82)
  • 1
    • 12844266861 scopus 로고    scopus 로고
    • Does independent component analysis play a role in unmixing hyperspectral data?
    • J. M. P. Nascimento and J. M. B. Dias, Does independent component analysis play a role in unmixing hyperspectral data? IEEE Transactions on Geoscience and Remote Sensing, vol. 43, no. 1, pp. 175-187, 2005.
    • (2005) IEEE Transactions on Geoscience and Remote Sensing , vol.43 , Issue.1 , pp. 175-187
    • Nascimento, J.M.P.1    Dias, J.M.B.2
  • 4
    • 14644412366 scopus 로고    scopus 로고
    • Classification of hyperspectral data from urban areas based on extended morphological profiles
    • J. Benediktsson, J. Palmason, and J. Sveinsson, Classification of hyperspectral data from urban areas based on extended morphological profiles, IEEE Transactions on Geoscience and Remote Sensing, vol. 43, no. 3, pp. 480-491, 2005.
    • (2005) IEEE Transactions on Geoscience and Remote Sensing , vol.43 , Issue.3 , pp. 480-491
    • Benediktsson, J.1    Palmason, J.2    Sveinsson, J.3
  • 5
    • 4344614511 scopus 로고    scopus 로고
    • Classification of hyperspectral remote sensing images with support vector machines
    • F. Melgani and L. Bruzzone, Classification of hyperspectral remote sensing images with support vector machines, IEEE Transactions on Geoscience and Remote Sensing, vol. 42, no. 8, pp. 1778-1790, 2004.
    • (2004) IEEE Transactions on Geoscience and Remote Sensing , vol.42 , Issue.8 , pp. 1778-1790
    • Melgani, F.1    Bruzzone, L.2
  • 6
    • 1942535080 scopus 로고    scopus 로고
    • SVM-based density estimation for supervised classification of remotely sensed images with unknown classes
    • in Proceedings of the SPIE Conference on Image and Signal Processing for Remote Sensing IX
    • P. Mantero, G. Moser, and S. B. Serpico, SVM-based density estimation for supervised classification of remotely sensed images with unknown classes, in Proceedings of the SPIE Conference on Image and Signal Processing for Remote Sensing IX, Vol. 5238, pp. 386-397, 2004.
    • (2004) , vol.5238 , pp. 386-397
    • Mantero, P.1    Moser, G.2    Serpico, S.B.3
  • 7
    • 85032751238 scopus 로고    scopus 로고
    • Signal processing for hyperspectral image exploitation
    • G. Shaw and D. Manolakis, Signal processing for hyperspectral image exploitation, IEEE Signal Processing Magazine, vol. 19, no. 1, pp. 12-16, 2002.
    • (2002) IEEE Signal Processing Magazine , vol.19 , Issue.1 , pp. 12-16
    • Shaw, G.1    Manolakis, D.2
  • 8
    • 85032751896 scopus 로고    scopus 로고
    • Hyperspectral image data analysis
    • D. Landgrebe, Hyperspectral image data analysis, IEEE Signal Processing Magazine, vol. 19, no. 1, pp. 17-28, 2002.
    • (2002) IEEE Signal Processing Magazine , vol.19 , Issue.1 , pp. 17-28
    • Landgrebe, D.1
  • 9
    • 0033686694 scopus 로고    scopus 로고
    • An algorithm taxonomy for hyperspectral unmixing
    • in Proceedings of the SPIE AeroSense Conference on Algorithms for Multispectral and Hyperspectral Imagery VI
    • N. Keshava, J. Kerekes, D. Manolakis, and G. Shaw, An algorithm taxonomy for hyperspectral unmixing, in Proceedings of the SPIE AeroSense Conference on Algorithms for Multispectral and Hyperspectral Imagery VI, Vol. 4049, pp. 42-63, 2000.
    • (2000) , vol.4049 , pp. 42-63
    • Keshava, N.1    Kerekes, J.2    Manolakis, D.3    Shaw, G.4
  • 10
    • 84930239955 scopus 로고    scopus 로고
    • Remote Sensing Digital Image Analysis: An Introduction
    • 4th edition, Springer, New York
    • J. A. Richards and X. Jia, Remote Sensing Digital Image Analysis: An Introduction, 4th edition, Springer, New York, 2005.
    • (2005)
    • Richards, J.A.1    Jia, X.2
  • 11
    • 84962942119 scopus 로고    scopus 로고
    • Mixed pixels classification
    • in Proceedings of the SPIE Conference on Image and Signal Processing for Remote Sensing IV
    • S. Liangrocapart and M. Petrou, Mixed pixels classification, in Proceedings of the SPIE Conference on Image and Signal Processing for Remote Sensing IV, Vol. 3500, pp. 72-83, 1998.
    • (1998) , vol.3500 , pp. 72-83
    • Liangrocapart, S.1    Petrou, M.2
  • 13
    • 0000186045 scopus 로고
    • Mars: Large scale mixing of bright and dark surface materials and implications for analysis of spectral reflectance
    • in Proceedings of the 10th Lunar and Planetary Science Conference
    • R. B. Singer and T. B. McCord, Mars: Large scale mixing of bright and dark surface materials and implications for analysis of spectral reflectance, in Proceedings of the 10th Lunar and Planetary Science Conference, pp. 1835-1848, 1979.
    • (1979) , pp. 1835-1848
    • Singer, R.B.1    McCord, T.B.2
  • 14
    • 0019679586 scopus 로고
    • Near-infrared spectral reflectance of mineral mixtures: Systematic combinations of pyroxenes, olivine, and iron oxides
    • R. Singer, Near-infrared spectral reflectance of mineral mixtures: Systematic combinations of pyroxenes, olivine, and iron oxides, Journal of Geophysical Research, vol. 86, pp. 7967-7982, 1981.
    • (1981) Journal of Geophysical Research , vol.86 , pp. 7967-7982
    • Singer, R.1
  • 15
    • 0001653435 scopus 로고
    • Spectral reflectance systematics for mixtures of powdered hypersthene, labradoride, and ilmenite
    • B. Nash and J. Conel, Spectral reflectance systematics for mixtures of powdered hypersthene, labradoride, and ilmenite, Journal of Geophysical Research, vol. 79, pp. 1615-1621, 1974.
    • (1974) Journal of Geophysical Research , vol.79 , pp. 1615-1621
    • Nash, B.1    Conel, J.2
  • 16
    • 0001473286 scopus 로고
    • Bidirection reflectance spectroscopy. I. theory
    • B. Hapke, Bidirection reflectance spectroscopy. I. theory, Journal of Geophysical Research, vol. 86, pp. 3039-3054, 1981.
    • (1981) Journal of Geophysical Research , vol.86 , pp. 3039-3054
    • Hapke, B.1
  • 17
    • 0021644332 scopus 로고
    • Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications
    • R. N. Clark and T. L. Roush, Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications, Journal of Geophysical Research, vol. 89, no. B7, pp. 6329-6340, 1984.
    • (1984) Journal of Geophysical Research , vol.89 , Issue.B7 , pp. 6329-6340
    • Clark, R.N.1    Roush, T.L.2
  • 18
    • 0028389048 scopus 로고
    • Nonlinear spectral mixing models for vegetative and soils surface
    • C. C. Borel and S. A. Gerstl, Nonlinear spectral mixing models for vegetative and soils surface, Remote Sensing of the Environment, vol. 47, no. 2, pp. 403-416, 1994.
    • (1994) Remote Sensing of the Environment , vol.47 , Issue.2 , pp. 403-416
    • Borel, C.C.1    Gerstl, S.A.2
  • 19
    • 0030189048 scopus 로고    scopus 로고
    • On the relationship between spectral unmixing and subspace projection
    • J. J. Settle, On the relationship between spectral unmixing and subspace projection, IEEE Transactions of Geoscience and Remote Sensing, vol. 34, pp. 1045-1046, 1996.
    • (1996) IEEE Transactions of Geoscience and Remote Sensing , vol.34 , pp. 1045-1046
    • Settle, J.J.1
  • 20
    • 0003984676 scopus 로고    scopus 로고
    • Hyperspectral Imaging: Techniques for Spectral Detection and Classification
    • Kluwer Academic, New York
    • C.-I. Chang, Hyperspectral Imaging: Techniques for Spectral Detection and Classification, Kluwer Academic, New York, 2003.
    • (2003)
    • Chang, C.-I.1
  • 21
    • 0023823045 scopus 로고
    • Image processing software for imaging spectrometry data analysis
    • A. S. Mazer, M. Martin, et al., Image processing software for imaging spectrometry data analysis, Remote Sensing of the Environment, vol. 24, no. 1, pp. 201-210, 1988.
    • (1988) Remote Sensing of the Environment , vol.24 , Issue.1 , pp. 201-210
    • Mazer, A.S.1    Martin, M.2
  • 22
    • 0001256711 scopus 로고
    • Discrimination among semi-arid landscape endmembres using the spectral angle mapper (SAM) algorithm
    • in Summaries of the 3rd Annual JPL Airborne Geoscience Workshop
    • R. H. Yuhas, A. F. H. Goetz, and J. W. Boardman, Discrimination among semi-arid landscape endmembres using the spectral angle mapper (SAM) algorithm, in Summaries of the 3rd Annual JPL Airborne Geoscience Workshop, edited by R. O. Green, Publication, 92-14, Vol. 1, pp. 147-149, 1992.
    • (1992) , vol.1 , pp. 147-149
    • Yuhas, R.H.1    Goetz, A.F.H.2    Boardman, J.W.3
  • 23
    • 0028467206 scopus 로고
    • Hyperspectral image classification and dimensionality reduction: An orthogonal subspace projection approach
    • J. C. Harsanyi and C.-I. Chang, Hyperspectral image classification and dimensionality reduction: An orthogonal subspace projection approach, IEEE Transactions Geoscience and Remote Sensing, vol. 32, no. 4, pp. 779-785, 1994.
    • (1994) IEEE Transactions Geoscience and Remote Sensing , vol.32 , Issue.4 , pp. 779-785
    • Harsanyi, J.C.1    Chang, C.-I.2
  • 24
    • 0006606953 scopus 로고    scopus 로고
    • Least squares subspace projection approach to mixed pixel classification for hyper-spectral images
    • C.-I. Chang, X. Zhao, M. L. G. Althouse, and J. J. Pan, Least squares subspace projection approach to mixed pixel classification for hyper-spectral images, IEEE Transactions on Geoscience and Remote Sensing, vol. 36, no. 3, pp. 898-912, 1998.
    • (1998) IEEE Transactions on Geoscience and Remote Sensing , vol.36 , Issue.3 , pp. 898-912
    • Chang, C.-I.1    Zhao, X.2    Althouse, M.L.G.3    Pan, J.J.4
  • 27
    • 0033224771 scopus 로고    scopus 로고
    • Hyperspectral data analysis and supervised feature reduction via projection pursuit
    • L. O. Jimenez and D. A. Landgrebe, Hyperspectral data analysis and supervised feature reduction via projection pursuit, IEEE Transactions on Geoscience and Remote Sensing, vol. 37, no. 6, pp. 2653-2664, 1999.
    • (1999) IEEE Transactions on Geoscience and Remote Sensing , vol.37 , Issue.6 , pp. 2653-2664
    • Jimenez, L.O.1    Landgrebe, D.A.2
  • 28
    • 0028416938 scopus 로고
    • Independent component analysis: A new concept
    • P. Common, Independent component analysis: A new concept, Signal Processing, vol. 36, pp. 287-314, 1994.
    • (1994) Signal Processing , vol.36 , pp. 287-314
    • Common, P.1
  • 29
    • 0003905759 scopus 로고    scopus 로고
    • Independent Component Analysis
    • John Wiley & Sons, New York
    • A. Hyvarinen, J. Karhunen, and E. Oja, Independent Component Analysis, John Wiley & Sons, New York, 2001.
    • (2001)
    • Hyvarinen, A.1    Karhunen, J.2    Oja, E.3
  • 30
    • 57649229726 scopus 로고    scopus 로고
    • Analysing hyperspectral data with independent component analysis
    • in Proceedings of the SPIE conference 26th AIPRWorkshop: Exploiting New Image Sources and Sensors
    • J. D. Bayliss, J. A. Gualtieri, and R. F. Cromp, Analysing hyperspectral data with independent component analysis, in Proceedings of the SPIE conference 26th AIPRWorkshop: Exploiting New Image Sources and Sensors, Vol. 3240, pp. 133-143, 1997.
    • (1997) , vol.3240 , pp. 133-143
    • Bayliss, J.D.1    Gualtieri, J.A.2    Cromp, R.F.3
  • 31
    • 0033312098 scopus 로고    scopus 로고
    • Independent component analysis for remote sensing study
    • in Proceedings of the SPIE Symposium on Remote Sensing Conference on Image and Signal Processing for Remote Sensing V
    • C. Chen and X. Zhang, Independent component analysis for remote sensing study, in Proceedings of the SPIE Symposium on Remote Sensing Conference on Image and Signal Processing for Remote Sensing V, Vol. 3871, pp. 150-158, 1999.
    • (1999) , vol.3871 , pp. 150-158
    • Chen, C.1    Zhang, X.2
  • 32
    • 0033752388 scopus 로고    scopus 로고
    • Unsupervised signature extraction and separation in hyperspectral images: A noise-adjusted fast independent component analysis approach
    • T. M. Tu, Unsupervised signature extraction and separation in hyperspectral images: A noise-adjusted fast independent component analysis approach, Optical Engineering of SPIE, vol. 39, no. 4, pp. 897-906, 2000.
    • (2000) Optical Engineering of SPIE , vol.39 , Issue.4 , pp. 897-906
    • Tu, T.M.1
  • 33
    • 0034543937 scopus 로고    scopus 로고
    • Unsupervised hyperspectral image analysis using independent component analysis
    • in Proceedings of the IEEE International Geoscience and Remote Sensing Symposium
    • S.-S. Chiang, C.-I. Chang, and I.W. Ginsberg, Unsupervised hyperspectral image analysis using independent component analysis, in Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2000.
    • (2000)
    • Chiang, S.-S.1    Chang, C.-I.2    Ginsberg, I.W.3
  • 34
    • 0035574287 scopus 로고    scopus 로고
    • Spectral unmixing of hyperspectral images with the independent component analysis and wavelet packets
    • in Proceedings of the IEEE International Geoscience and Remote Sensing Symposium
    • M. Lennon, M. Mouchot, G. Mercier, and L. Hubert-Moy, Spectral unmixing of hyperspectral images with the independent component analysis and wavelet packets, in Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2001.
    • (2001)
    • Lennon, M.1    Mouchot, M.2    Mercier, G.3    Hubert-Moy, L.4
  • 35
    • 12844249277 scopus 로고    scopus 로고
    • ICA aided linear spectral mixture analysis of agricultural remote sensing images
    • in Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation
    • N. Kosaka and Y. Kosugi, ICA aided linear spectral mixture analysis of agricultural remote sensing images, in Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation, pp. 221-226, 2003.
    • (2003) , pp. 221-226
    • Kosaka, N.1    Kosugi, Y.2
  • 36
    • 12844267980 scopus 로고    scopus 로고
    • Independent component analysis in spectral images
    • in Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation
    • V. Botchko, E. Berina, Z. Korotkaya, J. Parkkinen, and T. Jaaskelainen, Independent component analysis in spectral images, in Proceedings of the 4th International Symposium on Independent Component Analysis and Blind Signal Separation, pp. 203-207, 2003.
    • (2003) , pp. 203-207
    • Botchko, V.1    Berina, E.2    Korotkaya, Z.3    Parkkinen, J.4    Jaaskelainen, T.5
  • 37
    • 3543059899 scopus 로고    scopus 로고
    • Scene analysis and detection in thermal infrared remote sensing using independent component analysis
    • in Proceedings of SPIE, Conference on Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks II
    • B. R. Foy and J. Theiler, Scene analysis and detection in thermal infrared remote sensing using independent component analysis, in Proceedings of SPIE, Conference on Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks II, Vol. 5439, pp. 131-139, 2004.
    • (2004) , vol.5439 , pp. 131-139
    • Foy, B.R.1    Theiler, J.2
  • 38
    • 18844373945 scopus 로고    scopus 로고
    • ICA-aided mixed-pixel analysis of hyperspectral data in agricultural land
    • N. Kosaka, K. Uto, and Y. Kosugi, ICA-aided mixed-pixel analysis of hyperspectral data in agricultural land, IEEEGeoscienceRemote Sensing Letters, vol. 2, no. 2, pp. 220-224, 2005.
    • (2005) IEEEGeoscienceRemote Sensing Letters , vol.2 , Issue.2 , pp. 220-224
    • Kosaka, N.1    Uto, K.2    Kosugi, Y.3
  • 39
    • 0033561886 scopus 로고    scopus 로고
    • Independent factor analysis
    • H. Attias, Independent factor analysis, Neural Computation, vol. 11, no. 4, pp. 803-851, 1999.
    • (1999) Neural Computation , vol.11 , Issue.4 , pp. 803-851
    • Attias, H.1
  • 41
    • 0036762725 scopus 로고    scopus 로고
    • Spatial/spectral endmember extraction by multidimensional morphological operations
    • A. Plaza, P. Martinez, R. Perez, and J. Plaza, Spatial/spectral endmember extraction by multidimensional morphological operations, IEEE Transactions on Geoscience and Remote Sensing, vol. 40, no. 9, pp. 2025-2041, 2002.
    • (2002) IEEE Transactions on Geoscience and Remote Sensing , vol.40 , Issue.9 , pp. 2025-2041
    • Plaza, A.1    Martinez, P.2    Perez, R.3    Plaza, J.4
  • 42
    • 0002081183 scopus 로고
    • Automating spectral unmixing of AVIRIS data using convex geometry concepts
    • in Summaries of the Fourth Annual JPL Airborne Geoscience Workshop
    • J. Boardman, Automating spectral unmixing of AVIRIS data using convex geometry concepts, in Summaries of the Fourth Annual JPL Airborne Geoscience Workshop, JPL Publication 93-26, AVIRIS Workshop, Vol. 1, pp. 11-14, 1993.
    • (1993) , vol.1 , pp. 11-14
    • Boardman, J.1
  • 44
    • 16444373735 scopus 로고    scopus 로고
    • Vertex component analysis: A fast algorithm to unmix hyperspectral data
    • J. M. P. Nascimento and J. M. B. Dias, Vertex component analysis: A fast algorithm to unmix hyperspectral data, IEEE Transactions on Geoscience and Remote Sensing, vol. 43, no. 4, pp. 898-910, 2005.
    • (2005) IEEE Transactions on Geoscience and Remote Sensing , vol.43 , Issue.4 , pp. 898-910
    • Nascimento, J.M.P.1    Dias, J.M.B.2
  • 45
    • 0033310314 scopus 로고    scopus 로고
    • N-findr: An algorithm for fast autonomous spectral endmember determination in hyperspectral data
    • in Proceedings of the SPIE conference on Imaging Spectrometry V
    • M. E. Winter, N-findr: An algorithm for fast autonomous spectral endmember determination in hyperspectral data, in Proceedings of the SPIE conference on Imaging Spectrometry V, Vol. 3753, pp. 266-275, 1999.
    • (1999) , vol.3753 , pp. 266-275
    • Winter, M.E.1
  • 46
    • 0003946510 scopus 로고
    • Principal Component Analysis
    • Springer-Verlag, New York
    • I. T. Jolliffe, Principal Component Analysis, Springer-Verlag, New York, 1986.
    • (1986)
    • Jolliffe, I.T.1
  • 47
    • 0023854011 scopus 로고
    • A transformation for ordering multispectral data in terms of image quality with implications for noise removal
    • A. Green, M. Berman, P. Switzer, and M. D. Craig, A transformation for ordering multispectral data in terms of image quality with implications for noise removal, IEEE Transactions on Geoscience and Remote Sensing, vol. 26, no. 1, pp. 65-74, 1988.
    • (1988) IEEE Transactions on Geoscience and Remote Sensing , vol.26 , Issue.1 , pp. 65-74
    • Green, A.1    Berman, M.2    Switzer, P.3    Craig, M.D.4
  • 48
    • 0003611103 scopus 로고
    • Statistical Signal Processing, Detection Estimation and Time Series Analysis
    • Addison-Wesley, Reading, MA
    • L. L. Scharf, Statistical Signal Processing, Detection Estimation and Time Series Analysis, Addison-Wesley, Reading, MA, 1991.
    • (1991)
    • Scharf, L.L.1
  • 49
    • 33644508946 scopus 로고    scopus 로고
    • Estimation of signal subspace on hyperspectral data
    • in Proceedings of SPIE Conference on Image and Signal Processing for Remote Sensing XI, edited by, L. Bruzzone
    • J. M. B. Dias and J. M. P. Nascimento, Estimation of signal subspace on hyperspectral data, in Proceedings of SPIE Conference on Image and Signal Processing for Remote Sensing XI, Vol. 5982, edited by, L. Bruzzone, pp. 191-198, 2005.
    • (2005) , vol.5982 , pp. 191-198
    • Dias, J.M.B.1    Nascimento, J.M.P.2
  • 50
    • 0036917442 scopus 로고    scopus 로고
    • Information-theory-based band selection and utility evaluation for reflective spectral systems
    • in Proceedings of the SPIE Conference on Algorithms and Technologies for Multispectral
    • S. S. Shen and E. M. Bassett, Information-theory-based band selection and utility evaluation for reflective spectral systems, in Proceedings of the SPIE Conference on Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII, Vol. 4725, pp. 18-29, 2002.
    • (2002) , vol.4725 , pp. 18-29
    • Shen, S.S.1    Bassett, E.M.2
  • 51
    • 0001827496 scopus 로고    scopus 로고
    • Real-time analysis of hyperspectral data sets using NRL's ORASIS algorithm
    • in Proceedings of the SPIE Conference on Imaging Spectrometry III
    • J. H. Bowles, J. A. Antoniades, M. M. Baumback, J. M. Grossmann, D. Haas, P. J. Palmadesso, and J. Stracka, Real-time analysis of hyperspectral data sets using NRL's ORASIS algorithm, in Proceedings of the SPIE Conference on Imaging Spectrometry III, Vol. 3118, pp. 38-45, 1997.
    • (1997) , vol.3118 , pp. 38-45
    • Bowles, J.H.1    Antoniades, J.A.2    Baumback, M.M.3    Grossmann, J.M.4    Haas, D.5    Palmadesso, P.J.6    Stracka, J.7
  • 52
    • 12844252952 scopus 로고    scopus 로고
    • Spectral imaging for remote sensing
    • G. Shaw and H. Burke, Spectral imaging for remote sensing, Lincoln Laboratory Journal, vol. 14, no. 1, pp. 3-28, 2003.
    • (2003) Lincoln Laboratory Journal , vol.14 , Issue.1 , pp. 3-28
    • Shaw, G.1    Burke, H.2
  • 53
    • 0034504281 scopus 로고    scopus 로고
    • Statistics of target spectra in hsi scenes
    • in Proceedings of the SPIE Conference on Imaging Spectrometry VI
    • J. S. Tyo, J. Robertson, J.Wollenbecker, and R. C. Olsen, Statistics of target spectra in hsi scenes, in Proceedings of the SPIE Conference on Imaging Spectrometry VI, vol. 4132, pp. 306-314, 2000.
    • (2000) , vol.4132 , pp. 306-314
    • Tyo, J.S.1    Robertson, J.2    Wollenbecker, J.3    Olsen, R.C.4
  • 54
    • 0033225639 scopus 로고    scopus 로고
    • Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions
    • G. Healey and D. Slater, Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions, IEEE Transactions on Geoscience and Remote Sensing, vol. 37, no. 6, pp. 2706-2717, 1999.
    • (1999) IEEE Transactions on Geoscience and Remote Sensing , vol.37 , Issue.6 , pp. 2706-2717
    • Healey, G.1    Slater, D.2
  • 56
    • 0030676410 scopus 로고    scopus 로고
    • Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models
    • in Proceedings of the IEEE International Conference on Acoustics
    • E. Moulines, J.-F. Cardoso, and E. Gassiat, Maximum likelihood for blind separation and deconvolution of noisy signals using mixture models, in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol. 5, pp. 3617-3620, 1997.
    • (1997) , vol.5 , pp. 3617-3620
    • Moulines, E.1    Cardoso, J.-F.2    Gassiat, E.3
  • 57
    • 0000662435 scopus 로고
    • Atmospheric modeling for space measurements of ground reflectances, including bidirectional properties
    • D. Tanre, M. Herman, P. Deschamps, and A. de Leffe, Atmospheric modeling for space measurements of ground reflectances, including bidirectional properties, Applied Optics, vol. 18, pp. 3587-3594, 1979.
    • (1979) Applied Optics , vol.18 , pp. 3587-3594
    • Tanre, D.1    Herman, M.2    Deschamps, P.3    De Leffe, A.4
  • 59
    • 0003409571 scopus 로고
    • Fundamentals of Digital Image Processing
    • edited by E. Cliffs, Prentice Hall, Englewood Cliffs, NJ
    • A. K. Jain, Fundamentals of Digital Image Processing, edited by E. Cliffs, Prentice Hall, Englewood Cliffs, NJ, 1989.
    • (1989)
    • Jain, A.K.1
  • 60
    • 0003778941 scopus 로고    scopus 로고
    • An Introduction to Atmospheric Radiation
    • 2nd edition, Academic Press, New York
    • K. Liou, An Introduction to Atmospheric Radiation, 2nd edition, Academic Press, New York, 2002.
    • (2002)
    • Liou, K.1
  • 61
    • 0041451813 scopus 로고
    • Calibration of airborne imaging spectrometer data to percent reflectance using field spectral measurements
    • in Proceeding of the Nineteenth International Symposium on Remote Sensing of Environment 2, Ann Arbor, Michigan
    • D. Roberts, Y. Yamaguchi, and R. Lyon, Calibration of airborne imaging spectrometer data to percent reflectance using field spectral measurements, in Proceeding of the Nineteenth International Symposium on Remote Sensing of Environment 2, Ann Arbor, Michigan, pp. 679-688, 1985.
    • (1985) , pp. 679-688
    • Roberts, D.1    Yamaguchi, Y.2    Lyon, R.3
  • 63
    • 0001395470 scopus 로고
    • A new analysis of rock and soil types at the viking lander 1 site
    • J. B. Adams and M. O. Smith, A new analysis of rock and soil types at the viking lander 1 site. Journal of Geophysical Research, vol. 91, no. B8, pp. 8098-8112, 1986.
    • (1986) Journal of Geophysical Research , vol.91 , Issue.B8 , pp. 8098-8112
    • Adams, J.B.1    Smith, M.O.2
  • 64
    • 84983666110 scopus 로고
    • Theory of Reflectance and Emittance Spectroscopy
    • Cambridge University Press, Cambridge, U. K
    • B. Hapke, Theory of Reflectance and Emittance Spectroscopy, Cambridge University Press, Cambridge, U. K.: 1993.
    • (1993)
    • Hapke, B.1
  • 65
    • 0027632699 scopus 로고
    • Improved estimation of fraction images using partial image restoration
    • H.-H. Wu and R. A. Schowengerdt, Improved estimation of fraction images using partial image restoration, IEEE Transactions on Geoscience and Remote Sensing, vol. 31, no. 4, pp. 771-778, 1993.
    • (1993) IEEE Transactions on Geoscience and Remote Sensing , vol.31 , Issue.4 , pp. 771-778
    • Wu, H.-H.1    Schowengerdt, R.A.2
  • 66
    • 0033890553 scopus 로고    scopus 로고
    • Endmember bundles: A new approach to incorporating endmember variability into spectral mixture analysis
    • C. Bateson, G. Asner, and C. Wessman, Endmember bundles: A new approach to incorporating endmember variability into spectral mixture analysis, IEEE Transactions on Geoscience and Remote Sensing, vol. 38, pp. 1083-1094, 2000.
    • (2000) IEEE Transactions on Geoscience and Remote Sensing , vol.38 , pp. 1083-1094
    • Bateson, C.1    Asner, G.2    Wessman, C.3
  • 67
    • 84889818360 scopus 로고    scopus 로고
    • Spectral identification of image endmembers determined from AVIRIS data
    • in Summaries of the VII JPL Airborne Earth Science Workshop
    • F. Kruse, Spectral identification of image endmembers determined from AVIRIS data, in Summaries of the VII JPL Airborne Earth Science Workshop, 1998.
    • (1998)
    • Kruse, F.1
  • 68
    • 0001290987 scopus 로고
    • Automated spectral analysis: A geological example using AVIRIS data, northern grapevine mountains, Nevada
    • in Proceedings of the 10th Thematic Conference, Geologic Remote Sensing
    • J. Boardman and F. Kruse, Automated spectral analysis: A geological example using AVIRIS data, northern grapevine mountains, Nevada, in Proceedings of the 10th Thematic Conference, Geologic Remote Sensing, 1994.
    • (1994)
    • Boardman, J.1    Kruse, F.2
  • 69
    • 0000466122 scopus 로고    scopus 로고
    • Survey on independent component analysis
    • A. Hyvärinen, Survey on independent component analysis, Neural Computing Surveys, vol. 2, pp. 94-128, 1999.
    • (1999) Neural Computing Surveys , vol.2 , pp. 94-128
    • Hyvärinen, A.1
  • 70
    • 0042826822 scopus 로고    scopus 로고
    • Independent component analysis: Algorithms and applications
    • A. Hyvarinen and E. Oja, Independent component analysis: Algorithms and applications, Neural Networks, vol. 13, no. 4-5, pp. 411-430, 2000.
    • (2000) Neural Networks , vol.13 , Issue.4-5 , pp. 411-430
    • Hyvarinen, A.1    Oja, E.2
  • 71
    • 0031122399 scopus 로고    scopus 로고
    • Infomax and maximum likelihood of source separation
    • J. Cardoso, Infomax and maximum likelihood of source separation, IEEE Signal Processing Letters, vol. 4, no. 4, pp. 112-114, 1997.
    • (1997) IEEE Signal Processing Letters , vol.4 , Issue.4 , pp. 112-114
    • Cardoso, J.1
  • 72
    • 0000164689 scopus 로고
    • An information-maximization approach to blind separation and blind deconvolution
    • A. J. Bell and T. J. Sejnowski, An information-maximization approach to blind separation and blind deconvolution, Neural Computation, vol. 10, pp. 215-234, 1995.
    • (1995) Neural Computation , vol.10 , pp. 215-234
    • Bell, A.J.1    Sejnowski, T.J.2
  • 74
    • 84889281816 scopus 로고
    • Elements of Information Theory
    • John Wiley & Sons, New York
    • T. Cover and J. Thomas, Elements of Information Theory, John Wiley & Sons, New York, 1991.
    • (1991)
    • Cover, T.1    Thomas, J.2
  • 76
    • 84948109721 scopus 로고    scopus 로고
    • The EM Algorithm and Extensions
    • John Wiley &, Sons, New York
    • G. McLachlan and T. Krishnan, The EM Algorithm and Extensions., John Wiley &, Sons, New York, 1997.
    • (1997)
    • McLachlan, G.1    Krishnan, T.2
  • 77
    • 0004066260 scopus 로고    scopus 로고
    • Finite Mixture Models
    • John Wiley & Sons, New York
    • G. McLachlan and D. Peel, Finite Mixture Models, John Wiley & Sons, New York, 2000.
    • (2000)
    • McLachlan, G.1    Peel, D.2
  • 78
    • 0003752733 scopus 로고    scopus 로고
    • Classification of high dimensional data
    • Purdue University, Ph.D. Thesis and School of Electrical&Computer Engineering Technical Report TR-ECE 98-4
    • P.-F. Hsieh and D. Landgrebe, Classification of high dimensional data, Purdue University, Ph.D. Thesis and School of Electrical&Computer Engineering Technical Report TR-ECE 98-4, 1998.
    • (1998)
    • Hsieh, P.-F.1    Landgrebe, D.2
  • 79
    • 0003901853 scopus 로고    scopus 로고
    • Multispectral data analysis: A signal theory perspective
    • Purdue University, Technical Report
    • D. Landgrebe, Multispectral data analysis: A signal theory perspective, Purdue University, Technical Report, 1998.
    • (1998)
    • Landgrebe, D.1
  • 80
    • 38049152971 scopus 로고    scopus 로고
    • An EM algorithm for the estimation of dirichlet parameters
    • Instituto de Telecomunicações Technical Report
    • J. M. B. Dias, An EM algorithm for the estimation of dirichlet parameters, Instituto de Telecomunicações, http://www.lx.it.pt/~bioucas/, Technical Report, 2005.
    • (2005)
    • Dias, J.M.B.1
  • 81
    • 0004203240 scopus 로고    scopus 로고
    • The EM Algorithm and Extensions
    • John Wiley & Sons, New York
    • G. McLachlan and T. Krishnan, The EM Algorithm and Extensions., John Wiley & Sons, New York, 1996.
    • (1996)
    • McLachlan, G.1    Krishnan, T.2
  • 82
    • 0003751241 scopus 로고
    • The U.S. geological survey digital spectral library: Version 1: 0.2 to 3.0 mm
    • U.S. Geological Survey, Open File Report 93-592
    • R. N. Clark, G. A. Swayze, A. Gallagher, T. V. King, and W. M. Calvin, The U.S. geological survey digital spectral library: Version 1: 0.2 to 3.0 mm, U.S. Geological Survey, Open File Report 93-592, 1993.
    • (1993)
    • Clark, R.N.1    Swayze, G.A.2    Gallagher, A.3    King, T.V.4    Calvin, W.M.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.