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Volumn 46, Issue 10, 2015, Pages 2966-2977

Hyperspectral image classification via multitask joint sparse representation and stepwise MRF optimization

Author keywords

Hyperspectral image (HSI) classification; Markov random field (MRF); Multitask; Sparse representation

Indexed keywords

CLASSIFICATION (OF INFORMATION); LAND USE; MAGNETORHEOLOGICAL FLUIDS; MARINE APPLICATIONS; MARINE BIOLOGY; MARKOV PROCESSES; MULTITASKING; QUALITY CONTROL; REMOTE SENSING; SPECTROSCOPY; STRUCTURAL FRAMES;

EID: 84944593707     PISSN: 21682267     EISSN: 21682275     Source Type: Journal    
DOI: 10.1109/TCYB.2015.2484324     Document Type: Article
Times cited : (187)

References (55)
  • 2
    • 85027918174 scopus 로고    scopus 로고
    • Domain adaptation for remote sensing image classification: A low-rank reconstruction and instance weighting label propagation inspired algorithm
    • Oct.
    • Q. Shi, B. Du, and L. Zhang, "Domain adaptation for remote sensing image classification: A low-rank reconstruction and instance weighting label propagation inspired algorithm", IEEE Trans. Geosci. Remote Sens., vol. 53, no. 10, pp. 5677-5689, Oct. 2015.
    • (2015) IEEE Trans. Geosci. Remote Sens. , vol.53 , Issue.10 , pp. 5677-5689
    • Shi, Q.1    Du, B.2    Zhang, L.3
  • 3
    • 84927670473 scopus 로고    scopus 로고
    • Spatial coherence-based batch-mode active learning for remote sensing image classification
    • Jul
    • Q. Shi, B. Du, and L. Zhang, "Spatial coherence-based batch-mode active learning for remote sensing image classification", IEEE Trans. Image Process., vol. 24, no. 7, pp. 2037-2050, Jul. 2015.
    • (2015) IEEE Trans. Image Process. , vol.24 , Issue.7 , pp. 2037-2050
    • Shi, Q.1    Du, B.2    Zhang, L.3
  • 4
    • 56849127860 scopus 로고    scopus 로고
    • Spectral and spatial classification of hyperspectral data using SVMs and morphological profiles
    • Nov.
    • M. Fauvel, J. A. Benediktsson, J. Chanussot, and J. R. Sveinsson, "Spectral and spatial classification of hyperspectral data using SVMs and morphological profiles", IEEE Trans. Geosci. Remote Sens., vol. 46, no. 11, pp. 3804-3814, Nov. 2008.
    • (2008) IEEE Trans. Geosci. Remote Sens. , vol.46 , Issue.11 , pp. 3804-3814
    • Fauvel, M.1    Benediktsson, J.A.2    Chanussot, J.3    Sveinsson, J.R.4
  • 5
    • 85027941688 scopus 로고    scopus 로고
    • Novel two-dimensional singular spectrum analysis for effective feature extraction and data classification in hyperspectral imaging
    • Aug.
    • J. Zabalza et al., "Novel two-dimensional singular spectrum analysis for effective feature extraction and data classification in hyperspectral imaging", IEEE Trans. Geosci. Remote Sens., vol. 53, no. 8, pp. 4418-4433, Aug. 2015.
    • (2015) IEEE Trans. Geosci. Remote Sens. , vol.53 , Issue.8 , pp. 4418-4433
    • Zabalza, J.1
  • 8
    • 84890054595 scopus 로고    scopus 로고
    • The relevance sample-feature machine: A sparse Bayesian learning approach to joint feature-sample selection
    • Dec.
    • Y. Mohsenzadeh, H. Sheikhzadeh, A. M. Reza, N. Bathaee, and M. M. Kalayeh, "The relevance sample-feature machine: A sparse Bayesian learning approach to joint feature-sample selection", IEEE Trans. Cybern., vol. 43, no. 6, pp. 2241-2254, Dec. 2013.
    • (2013) IEEE Trans. Cybern. , vol.43 , Issue.6 , pp. 2241-2254
    • Mohsenzadeh, Y.1    Sheikhzadeh, H.2    Reza, A.M.3    Bathaee, N.4    Kalayeh, M.M.5
  • 9
    • 36048992886 scopus 로고    scopus 로고
    • General tensor discriminant analysis and Gabor features for gait recognition
    • Oct.
    • D. Tao, X. Li, X. Wu, and S. J. Maybank, "General tensor discriminant analysis and Gabor features for gait recognition", IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 10, pp. 1700-1715, Oct. 2007.
    • (2007) IEEE Trans. Pattern Anal. Mach. Intell. , vol.29 , Issue.10 , pp. 1700-1715
    • Tao, D.1    Li, X.2    Wu, X.3    Maybank, S.J.4
  • 10
    • 84877887638 scopus 로고    scopus 로고
    • Multiview Hessian regularization for image annotation
    • Jul
    • W. Liu and D. Tao, "Multiview Hessian regularization for image annotation", IEEE Trans. Image Process., vol. 22, no. 7, pp. 2676-2687, Jul. 2013.
    • (2013) IEEE Trans. Image Process. , vol.22 , Issue.7 , pp. 2676-2687
    • Liu, W.1    Tao, D.2
  • 11
    • 84928379855 scopus 로고    scopus 로고
    • Multi-task pose-invariant face recognition
    • Mar.
    • C. Ding, C. Xu, and D. Tao, "Multi-task pose-invariant face recognition", IEEE Trans. Image Process., vol. 24, no. 3, pp. 980-993, Mar. 2015.
    • (2015) IEEE Trans. Image Process. , vol.24 , Issue.3 , pp. 980-993
    • Ding, C.1    Xu, C.2    Tao, D.3
  • 12
    • 84866609133 scopus 로고    scopus 로고
    • Visual classification with multitask joint sparse representation
    • Oct.
    • X.-T. Yuan, X. Liu, and S. Yan, "Visual classification with multitask joint sparse representation", IEEE Trans. Image Process., vol. 21, no. 10, pp. 4349-4360, Oct. 2012.
    • (2012) IEEE Trans. Image Process. , vol.21 , Issue.10 , pp. 4349-4360
    • Yuan, X.-T.1    Liu, X.2    Yan, S.3
  • 13
    • 84872258670 scopus 로고    scopus 로고
    • Manifold regularized multitask learning for semi-supervised multilabel image classification
    • Feb.
    • Y. Luo, D. Tao, C. Xu, B. Geng, and S. J. Maybank, "Manifold regularized multitask learning for semi-supervised multilabel image classification", IEEE Trans. Image Process., vol. 22, no. 2, pp. 523-536, Feb. 2013.
    • (2013) IEEE Trans. Image Process. , vol.22 , Issue.2 , pp. 523-536
    • Luo, Y.1    Tao, D.2    Xu, C.3    Geng, B.4    Maybank, S.J.5
  • 14
    • 84904192140 scopus 로고    scopus 로고
    • Large-margin multi-viewinformation bottleneck
    • Aug.
    • C. Xu, D. Tao, and C. Xu, "Large-margin multi-viewinformation bottleneck", IEEE Trans. Pattern Anal. Mach. Intell., vol. 36, no. 8, pp. 1559-1572, Aug. 2014.
    • (2014) IEEE Trans. Pattern Anal. Mach. Intell. , vol.36 , Issue.8 , pp. 1559-1572
    • Xu, C.1    Tao, D.2    Xu, C.3
  • 15
    • 84896389249 scopus 로고    scopus 로고
    • Kernel sparse multitask learning for hyperspectral image classification with empirical mode decomposition and morphological wavelet-based features
    • Aug.
    • H. Zhi, Q. Wang, Y. Shen, and M. Sun, "Kernel sparse multitask learning for hyperspectral image classification with empirical mode decomposition and morphological wavelet-based features", IEEE Trans. Geosci. Remote Sens., vol. 52, no. 8, pp. 5150-5163, Aug. 2014.
    • (2014) IEEE Trans. Geosci. Remote Sens. , vol.52 , Issue.8 , pp. 5150-5163
    • Zhi, H.1    Wang, Q.2    Shen, Y.3    Sun, M.4
  • 16
    • 84901201294 scopus 로고    scopus 로고
    • Joint collaborative representation with multitask learning for hyperspectral image classification
    • Sep.
    • J. Li, H. Zhang, L. Zhang, X. Huang, and L. Zhang, "Joint collaborative representation with multitask learning for hyperspectral image classification", IEEE Trans. Geosci. Remote Sens., vol. 52, no. 9, pp. 5923-5936, Sep. 2014.
    • (2014) IEEE Trans. Geosci. Remote Sens. , vol.52 , Issue.9 , pp. 5923-5936
    • Li, J.1    Zhang, H.2    Zhang, L.3    Huang, X.4    Zhang, L.5
  • 18
    • 84255182564 scopus 로고    scopus 로고
    • Support vector machines, import vector machines and relevance vector machines for hyperspectral classification-A comparison
    • Lisbon, Portugal
    • A. C. Braun, U. Weidner, and S. Hinz, "Support vector machines, import vector machines and relevance vector machines for hyperspectral classification-A comparison", in Proc. IEEE 3rd Workshop Hyperspect. Image Signal Process. Evol. Remote Sens., Lisbon, Portugal, 2011, pp. 1-4.
    • (2011) Proc. IEEE 3rd Workshop Hyperspect. Image Signal Process. Evol. Remote Sens. , pp. 1-4
    • Braun, A.C.1    Weidner, U.2    Hinz, S.3
  • 19
    • 67650436064 scopus 로고    scopus 로고
    • Recent advances in techniques for hyperspectral image processing
    • Sep.
    • A. Plaza et al., "Recent advances in techniques for hyperspectral image processing", Remote Sens. Environ., vol. 113, pp. S110-S122, Sep. 2009.
    • (2009) Remote Sens. Environ. , vol.113 , pp. S110-S122
    • Plaza, A.1
  • 20
    • 80955154956 scopus 로고    scopus 로고
    • Hyperspectral image classification using spectral and spatial information based linear discriminant analysis
    • Vancouver, BC, Canada
    • C.-H. Li, H.-S. Chu, B.-C. Kuo, and C.-T. Lin, "Hyperspectral image classification using spectral and spatial information based linear discriminant analysis", in Proc. IEEE Int. Geosci. Remote Sens. Symp., Vancouver, BC, Canada, 2011, pp. 1716-1719.
    • (2011) Proc. IEEE Int. Geosci. Remote Sens. Symp. , pp. 1716-1719
    • Li, C.-H.1    Chu, H.-S.2    Kuo, B.-C.3    Lin, C.-T.4
  • 21
    • 84891559599 scopus 로고    scopus 로고
    • Spectral-spatial constraint hyperspectral image classification
    • Mar.
    • R. Ji et al., "Spectral-spatial constraint hyperspectral image classification", IEEE Trans. Geosci. Remote Sens., vol. 52, no. 3, pp. 1811-1823, Mar. 2014.
    • (2014) IEEE Trans. Geosci. Remote Sens. , vol.52 , Issue.3 , pp. 1811-1823
    • Ji, R.1
  • 22
    • 84896314121 scopus 로고    scopus 로고
    • Spectral-spatial hyperspectral image classification with edge-preserving filtering
    • May
    • X. Kang, S. Li, and J. A. Benediktsson, "Spectral-spatial hyperspectral image classification with edge-preserving filtering", IEEE Trans. Geosci. Remote Sens., vol. 52, no. 5, pp. 2666-2677, May 2014.
    • (2014) IEEE Trans. Geosci. Remote Sens. , vol.52 , Issue.5 , pp. 2666-2677
    • Kang, X.1    Li, S.2    Benediktsson, J.A.3
  • 23
    • 84937469063 scopus 로고    scopus 로고
    • In defense of iterated conditional mode for hyperspectral image classification
    • Chengdu, China
    • J. Lin, Q. Wang, and Y. Yuan, "In defense of iterated conditional mode for hyperspectral image classification", in Proc. IEEE Int. Conf. Multimedia Expo, Chengdu, China, 2014, pp. 1-6.
    • (2014) Proc. IEEE Int. Conf. Multimedia Expo , pp. 1-6
    • Lin, J.1    Wang, Q.2    Yuan, Y.3
  • 24
    • 77958017904 scopus 로고    scopus 로고
    • SVM- and MRF-based method for accurate classification of hyperspectral images
    • Oct.
    • Y. Tarabalka, M. Fauvel, J. Chanussot, and J. A. Benediktsson, "SVM- and MRF-based method for accurate classification of hyperspectral images", IEEE Trans. Geosci. Remote Sens., vol. 7, no. 4, pp. 736-740, Oct. 2010.
    • (2010) IEEE Trans. Geosci. Remote Sens. , vol.7 , Issue.4 , pp. 736-740
    • Tarabalka, Y.1    Fauvel, M.2    Chanussot, J.3    Benediktsson, J.A.4
  • 25
    • 80052335044 scopus 로고    scopus 로고
    • Adaptive Markov random field approach for classification of hyperspectral imagery
    • Sep.
    • B. Zhang, S. Li, X. Jia, L. Gao, and M. Peng, "Adaptive Markov random field approach for classification of hyperspectral imagery", IEEE Geosci. Remote Sens. Lett., vol. 8, no. 5, pp. 973-977, Sep. 2011.
    • (2011) IEEE Geosci. Remote Sens. Lett. , vol.8 , Issue.5 , pp. 973-977
    • Zhang, B.1    Li, S.2    Jia, X.3    Gao, L.4    Peng, M.5
  • 26
    • 80052087931 scopus 로고    scopus 로고
    • Spectral-spatial hyperspectral image segmentation using subspace multinomial logistic regression and Markov random fields
    • Mar.
    • J. Li, J. M. Bioucas-Dias, and A. Plaza, "Spectral-spatial hyperspectral image segmentation using subspace multinomial logistic regression and Markov random fields", IEEE Geosci. Remote Sens. Lett., vol. 50, no. 3, pp. 809-823, Mar. 2012.
    • (2012) IEEE Geosci. Remote Sens. Lett. , vol.50 , Issue.3 , pp. 809-823
    • Li, J.1    Bioucas-Dias, J.M.2    Plaza, A.3
  • 27
  • 29
    • 77951295936 scopus 로고    scopus 로고
    • Feature selection for classification of hyperspectral data by SVM
    • May
    • M. Pal and G. M. Foody, "Feature selection for classification of hyperspectral data by SVM", IEEE Trans. Geosci. Remote Sens., vol. 48, no. 5, pp. 2297-2307, May 2010.
    • (2010) IEEE Trans. Geosci. Remote Sens. , vol.48 , Issue.5 , pp. 2297-2307
    • Pal, M.1    Foody, G.M.2
  • 30
    • 77958017904 scopus 로고    scopus 로고
    • SVMand MRF-based method for accurate classification of hyperspectral images
    • Oct.
    • Y. Tarabalka, M. Fauvel, J. Chanussot, and J. A. Benediktsson, "SVMand MRF-based method for accurate classification of hyperspectral images", IEEE Geosci. Remote Sens. Lett., vol. 7, no. 4, pp. 736-740, Oct. 2010.
    • (2010) IEEE Geosci. Remote Sens. Lett. , vol.7 , Issue.4 , pp. 736-740
    • Tarabalka, Y.1    Fauvel, M.2    Chanussot, J.3    Benediktsson, J.A.4
  • 31
    • 77952717202 scopus 로고    scopus 로고
    • Sparse representation for computer vision and pattern recognition
    • Jun.
    • J. Wright et al., "Sparse representation for computer vision and pattern recognition", Proc. IEEE, vol. 98, no. 6, pp. 1031-1044, Jun. 2010.
    • (2010) Proc. IEEE , vol.98 , Issue.6 , pp. 1031-1044
    • Wright, J.1
  • 32
    • 84886598638 scopus 로고    scopus 로고
    • Saliency detection by multipleinstance learning
    • Apr.
    • Q. Wang, Y. Yuan, P. Yan, and X. Li, "Saliency detection by multipleinstance learning", IEEE Trans. Cybern., vol. 43, no. 2, pp. 660-672, Apr. 2013.
    • (2013) IEEE Trans. Cybern. , vol.43 , Issue.2 , pp. 660-672
    • Wang, Q.1    Yuan, Y.2    Yan, P.3    Li, X.4
  • 33
    • 84869127088 scopus 로고    scopus 로고
    • Multi-spectral saliency detection
    • Q. Wang, P. Yan, Y. Yuan, and X. Li, "Multi-spectral saliency detection", Pattern Recognit. Lett., vol. 34, no. 1, pp. 34-41, 2013.
    • (2013) Pattern Recognit. Lett. , vol.34 , Issue.1 , pp. 34-41
    • Wang, Q.1    Yan, P.2    Yuan, Y.3    Li, X.4
  • 35
    • 77951173993 scopus 로고    scopus 로고
    • Accelerated gradient method for multi-task sparse learning problem
    • Miami, FL, USA
    • X. Chen, W. Pan, J. T. Kwok, and J. G. Carbonell, "Accelerated gradient method for multi-task sparse learning problem", in Proc. IEEE 9th Int. Conf. Data Mining, Miami, FL, USA, 2009, pp. 746-751.
    • (2009) Proc. IEEE 9th Int. Conf. Data Mining , pp. 746-751
    • Chen, X.1    Pan, W.2    Kwok, J.T.3    Carbonell, J.G.4
  • 36
    • 85027928537 scopus 로고    scopus 로고
    • Ordinal regression by a generalized force-based model
    • Apr.
    • F. Fernandez-Navarro, A. Riccardi, and S. Carloni, "Ordinal regression by a generalized force-based model", IEEE Trans. Cybern., vol. 45, no. 4, pp. 844-857, Apr. 2015.
    • (2015) IEEE Trans. Cybern. , vol.45 , Issue.4 , pp. 844-857
    • Fernandez-Navarro, F.1    Riccardi, A.2    Carloni, S.3
  • 37
    • 84928400696 scopus 로고    scopus 로고
    • Adaptive distributed outlier detection for WSNs
    • May
    • A. De Paola, S. Gaglio, G. L. Re, and F. Milazzo, "Adaptive distributed outlier detection for WSNs", IEEE Trans. Cybern., vol. 45, no. 5, pp. 888-899, May 2015.
    • (2015) IEEE Trans. Cybern. , vol.45 , Issue.5 , pp. 888-899
    • De Paola, A.1    Gaglio, S.2    Re, G.L.3    Milazzo, F.4
  • 40
    • 20444500972 scopus 로고    scopus 로고
    • A Bayesian MRF framework for labeling terrain using hyperspectral imaging
    • Jun.
    • R. Neher and A. Srivastava, "A Bayesian MRF framework for labeling terrain using hyperspectral imaging", IEEE Trans. Geosci. Remote Sens., vol. 43, no. 6, pp. 1363-1374, Jun. 2005.
    • (2005) IEEE Trans. Geosci. Remote Sens. , vol.43 , Issue.6 , pp. 1363-1374
    • Neher, R.1    Srivastava, A.2
  • 41
    • 85027944157 scopus 로고    scopus 로고
    • The generalization ability of SVM classification based on Markov sampling
    • Jun.
    • J. Xu et al., "The generalization ability of SVM classification based on Markov sampling", IEEE Trans. Cybern., vol. 45, no. 6, pp. 1169-1179, Jun. 2015.
    • (2015) IEEE Trans. Cybern. , vol.45 , Issue.6 , pp. 1169-1179
    • Xu, J.1
  • 43
    • 0034546236 scopus 로고    scopus 로고
    • Comparison of Gaussian mixture and linear mixture models for classification of hyperspectral data
    • Honolulu, HI, USA
    • S. G. Beaven, D. Stein, and L. E. Hoff, "Comparison of Gaussian mixture and linear mixture models for classification of hyperspectral data", in Proc. IEEE Int. Geosci. Remote Sens. Symp., vol. 4. Honolulu, HI, USA, 2000, pp. 1597-1599.
    • (2000) Proc. IEEE Int. Geosci. Remote Sens. Symp. , vol.4 , pp. 1597-1599
    • Beaven, S.G.1    Stein, D.2    Hoff, L.E.3
  • 44
    • 43249091850 scopus 로고    scopus 로고
    • A comparative study of energy minimization methods for Markov random fields with smoothness-based priors
    • Jun.
    • R. Szeliski et al., "A comparative study of energy minimization methods for Markov random fields with smoothness-based priors", IEEE Trans. Pattern Anal. Mach. Intell., vol. 30, no. 6, pp. 1068-1080, Jun. 2008.
    • (2008) IEEE Trans. Pattern Anal. Mach. Intell. , vol.30 , Issue.6 , pp. 1068-1080
    • Szeliski, R.1
  • 45
    • 85027932710 scopus 로고    scopus 로고
    • Parameter selection of Gaussian kernel for one-class SVM
    • May
    • Y. Xiao, H. Wang, and W. Xu, "Parameter selection of Gaussian kernel for one-class SVM", IEEE Trans. Cybern., vol. 45, no. 5, pp. 927-939, May 2015.
    • (2015) IEEE Trans. Cybern. , vol.45 , Issue.5 , pp. 927-939
    • Xiao, Y.1    Wang, H.2    Xu, W.3
  • 46
    • 79952039898 scopus 로고    scopus 로고
    • Surveying and comparing simultaneous sparse approximation or group-lasso algorithms
    • A. Rakotomamonjy, "Surveying and comparing simultaneous sparse approximation or group-lasso algorithms", Signal Process., vol. 91, no. 7, pp. 1505-1526, 2011.
    • (2011) Signal Process. , vol.91 , Issue.7 , pp. 1505-1526
    • Rakotomamonjy, A.1
  • 47
    • 77949732443 scopus 로고    scopus 로고
    • Signal recovery from incomplete and inaccurate measurements via regularized orthogonal matching pursuit
    • Apr.
    • D. Needell and R. Vershynin, "Signal recovery from incomplete and inaccurate measurements via regularized orthogonal matching pursuit", IEEE J. Sel. Topics Signal Process., vol. 4, no. 2, pp. 310-316, Apr. 2010.
    • (2010) IEEE J. Sel. Topics Signal Process. , vol.4 , Issue.2 , pp. 310-316
    • Needell, D.1    Vershynin, R.2
  • 48
    • 0040528764 scopus 로고
    • Multinomial logistic regression algorithm
    • D. Böhning, "Multinomial logistic regression algorithm", Ann. Inst. Stat. Math., vol. 44, no. 1, pp. 197-200, 1992.
    • (1992) Ann. Inst. Stat. Math. , vol.44 , Issue.1 , pp. 197-200
    • Böhning, D.1
  • 49
    • 78049282844 scopus 로고    scopus 로고
    • Semisupervised hyperspectral image segmentation using multinomial logistic regression with active learning
    • Nov.
    • J. Li, J. M. Bioucas-Dias, and A. Plaza, "Semisupervised hyperspectral image segmentation using multinomial logistic regression with active learning", IEEE Trans. Geosci. Remote Sens., vol. 48, no. 11, pp. 4085-4098, Nov. 2010.
    • (2010) IEEE Trans. Geosci. Remote Sens. , vol.48 , Issue.11 , pp. 4085-4098
    • Li, J.1    Bioucas-Dias, J.M.2    Plaza, A.3
  • 50
    • 65749110333 scopus 로고    scopus 로고
    • Subspace pursuit for compressive sensing signal reconstruction
    • May
    • W. Dai and O. Milenkovic, "Subspace pursuit for compressive sensing signal reconstruction", IEEE Trans. Inf. Theory, vol. 55, no. 2, pp. 2230-2249, May 2009.
    • (2009) IEEE Trans. Inf. Theory , vol.55 , Issue.2 , pp. 2230-2249
    • Dai, W.1    Milenkovic, O.2
  • 51
    • 0036132565 scopus 로고    scopus 로고
    • Genetic feature selection combined with composite fuzzy nearest neighbor classifiers for hyperspectral satellite imagery
    • S. Yu, S. De Backer, and P. Scheunders, "Genetic feature selection combined with composite fuzzy nearest neighbor classifiers for hyperspectral satellite imagery", Pattern Recognit. Lett., vol. 23, nos. 1-3, pp. 183-190, 2002.
    • (2002) Pattern Recognit. Lett. , vol.23 , Issue.1-3 , pp. 183-190
    • Yu, S.1    De Backer, S.2    Scheunders, P.3
  • 52
    • 78049264379 scopus 로고    scopus 로고
    • Local manifold learning-basednearestneighbor for hyperspectral image classification
    • Nov.
    • L. Ma, M. M. Crawford, and J. Tian, "Local manifold learning-basednearestneighbor for hyperspectral image classification", IEEE Trans. Geosci. Remote Sens., vol. 48, no. 11, pp. 4099-4109, Nov. 2010.
    • (2010) IEEE Trans. Geosci. Remote Sens. , vol.48 , Issue.11 , pp. 4099-4109
    • Ma, L.1    Crawford, M.M.2    Tian, J.3
  • 53
    • 67949115614 scopus 로고    scopus 로고
    • Spectral-spatial classification of hyperspectral imagery based on partitional clustering techniques
    • Aug.
    • Y. Tarabalka, J. A. Benediktsson, and J. Chanussot, "Spectral-spatial classification of hyperspectral imagery based on partitional clustering techniques", IEEE Trans. Geosci. Remote Sens., vol. 47, no. 8, pp. 2973-2987, Aug. 2009.
    • (2009) IEEE Trans. Geosci. Remote Sens. , vol.47 , Issue.8 , pp. 2973-2987
    • Tarabalka, Y.1    Benediktsson, J.A.2    Chanussot, J.3
  • 54
    • 56849127860 scopus 로고    scopus 로고
    • Spectral and spatial classification of hyperspectral data using SVMs and morphological profiles
    • Nov.
    • M. Fauvel, J. A. Benediktsson, J. Chanussot, and J. R. Sveinsson, "Spectral and spatial classification of hyperspectral data using SVMs and morphological profiles", IEEE Trans. Geosci. Remote Sens., vol. 46, no. 11, pp. 3804-3814, Nov. 2008.
    • (2008) IEEE Trans. Geosci. Remote Sens. , vol.46 , Issue.11 , pp. 3804-3814
    • Fauvel, M.1    Benediktsson, J.A.2    Chanussot, J.3    Sveinsson, J.R.4
  • 55
    • 84859048363 scopus 로고    scopus 로고
    • Spectral-spatial classification of hyperspectral data based on a stochastic minimum spanning forest approach
    • Apr.
    • K. Bernard, Y. Tarabalka, J. Angulo, J. Chanussot, and J. A. Benediktsson, "Spectral-spatial classification of hyperspectral data based on a stochastic minimum spanning forest approach", IEEE Trans. Image Process., vol. 21, no. 4, pp. 2008-2021, Apr. 2012.
    • (2012) IEEE Trans. Image Process. , vol.21 , Issue.4 , pp. 2008-2021
    • Bernard, K.1    Tarabalka, Y.2    Angulo, J.3    Chanussot, J.4    Benediktsson, J.A.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.