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Volumn 54, Issue 4, 2015, Pages 707-716

Use of customizing kernel sparse representation for hyperspectral image classification

Author keywords

[No Author keywords available]

Indexed keywords

REMOTE SENSING; SPECTROSCOPY;

EID: 84942374193     PISSN: 1559128X     EISSN: 21553165     Source Type: Journal    
DOI: 10.1364/AO.54.000707     Document Type: Article
Times cited : (2)

References (32)
  • 1
    • 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 Trans. Geosci. Remote Sens. 42, 1778-1790 (2004).
    • (2004) IEEE Trans. Geosci. Remote Sens. , vol.42 , pp. 1778-1790
    • Melgani, F.1    Bruzzone, L.2
  • 2
    • 84555223724 scopus 로고    scopus 로고
    • Use of weighting algorithms to improve traditional support vector machine based classifications of relflectance data
    • B. Qi, C. Zhao, E. Youn, and C. Nansen, "Use of weighting algorithms to improve traditional support vector machine based classifications of relflectance data," Opt. Express 19, 26816-26826 (2011).
    • (2011) Opt. Express , vol.19 , pp. 26816-26826
    • Qi, B.1    Zhao, C.2    Youn, E.3    Nansen, C.4
  • 3
    • 41849112041 scopus 로고    scopus 로고
    • Customizing kernel functions for SVM-based hyperspectral image classification
    • B. Guo, S. R. Gunn, R. I. Damper, and J. D. B. Nelson, "Customizing kernel functions for SVM-based hyperspectral image classification," IEEE Trans. Image Process. 17, 622-629 (2008).
    • (2008) IEEE Trans. Image Process. , vol.17 , pp. 622-629
    • Guo, B.1    Gunn, S.R.2    Damper, R.I.3    Nelson, J.D.B.4
  • 4
    • 84942368799 scopus 로고    scopus 로고
    • Feature weighting algorithms for classification of hyperspectral images using a support vector machine
    • B. Qi, C. Zhao, and G. Yin, "Feature weighting algorithms for classification of hyperspectral images using a support vector machine," Appl. Opt. 53, 2839-2846 (2014).
    • (2014) Appl. Opt. , vol.53 , pp. 2839-2846
    • Qi, B.1    Zhao, C.2    Yin, G.3
  • 5
    • 56849127860 scopus 로고    scopus 로고
    • Spectral and spatial classification of hyperspectral data using SVMs and morphological profiles
    • 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. 46, 3804-3814 (2008).
    • (2008) IEEE Trans. Geosci. Remote Sens. , vol.46 , pp. 3804-3814
    • Fauvel, M.1    Benediktsson, J.A.2    Chanussot, J.3    Sveinsson, J.R.4
  • 6
    • 34249753618 scopus 로고
    • Support-vector networks
    • C. Cortes and V. Vapnik, "Support-vector networks," Mach. Learn. 20, 273-297 (1995).
    • (1995) Mach. Learn. , vol.20 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 7
    • 77951295936 scopus 로고    scopus 로고
    • Feature selection for classification of hyperspectral data by SVM
    • M. Pal and G. M. Foody, "Feature selection for classification of hyperspectral data by SVM," IEEE Trans. Geosci. Remote Sens. 48, 2297-2307 (2010).
    • (2010) IEEE Trans. Geosci. Remote Sens. , vol.48 , pp. 2297-2307
    • Pal, M.1    Foody, G.M.2
  • 8
    • 33750798496 scopus 로고    scopus 로고
    • Toward an optimal SVM classification system for hyperspectral remote sensing images
    • Y. Bazi and F. Melgani, "Toward an optimal SVM classification system for hyperspectral remote sensing images," IEEE Trans. Geosci. Remote Sens. 44, 3374-3385 (2006).
    • (2006) IEEE Trans. Geosci. Remote Sens. , vol.44 , pp. 3374-3385
    • Bazi, Y.1    Melgani, F.2
  • 10
    • 84899990796 scopus 로고    scopus 로고
    • Optimizing subspace SVM ensemble for hyperspectral imagery classification
    • Y. Chen, X. Zhao, and Z. Lin, "Optimizing subspace SVM ensemble for hyperspectral imagery classification," IEEE J. Sel. Topics Appl. Earth Obs. Remote Sens. 7, 1295-1305 (2014).
    • (2014) IEEE J. Sel. Topics Appl. Earth Obs. Remote Sens. , vol.7 , pp. 1295-1305
    • Chen, Y.1    Zhao, X.2    Lin, Z.3
  • 11
    • 84905910095 scopus 로고    scopus 로고
    • Harmonic analysis for hyperspectral image classification integrated with PSO optimized SVM
    • Z. Xue, P. Du, and H. Su, "Harmonic analysis for hyperspectral image classification integrated with PSO optimized SVM," IEEE J. Sel. Topics Appl. Earth Obs. Remote Sens. 7, 2131-2146 (2014).
    • (2014) IEEE J. Sel. Topics Appl. Earth Obs. Remote Sens. , vol.7 , pp. 2131-2146
    • Xue, Z.1    Du, P.2    Su, H.3
  • 12
    • 84879991207 scopus 로고    scopus 로고
    • Contextual SVM using Hilbert space embedding for hyperspectral classification
    • P. Gurram and H. Kwon, "Contextual SVM using Hilbert space embedding for hyperspectral classification," IEEE Geosci. Remote Sens. Lett. 10, 1031-1035 (2013).
    • (2013) IEEE Geosci. Remote Sens. Lett. , vol.10 , pp. 1031-1035
    • Gurram, P.1    Kwon, H.2
  • 13
    • 84899919914 scopus 로고    scopus 로고
    • A novel hierarchical semisupervised SVM for classification of hyperspectral images
    • Z. Shao, L. Zhang, X. Zhou, and L. Ding, "A novel hierarchical semisupervised SVM for classification of hyperspectral images," IEEE Geosci. Remote Sens. Lett. 11, 1609-1613 (2014).
    • (2014) IEEE Geosci. Remote Sens. Lett. , vol.11 , pp. 1609-1613
    • Shao, Z.1    Zhang, L.2    Zhou, X.3    Ding, L.4
  • 14
    • 84880301480 scopus 로고    scopus 로고
    • Optimized Laplacian SVM with distance metric learning for hyperspectral image classification
    • Y. Gu and K. Feng, "Optimized Laplacian SVM with distance metric learning for hyperspectral image classification," IEEE J. Sel. Topics Appl. Earth Obs. Remote Sens. 6, 1109-1117 (2013).
    • (2013) IEEE J. Sel. Topics Appl. Earth Obs. Remote Sens. , vol.6 , pp. 1109-1117
    • Gu, Y.1    Feng, K.2
  • 17
    • 84904285443 scopus 로고    scopus 로고
    • Group-based sparse representation for image restoration
    • J. Zhang, D. Zhao, and W. Gao, "Group-based sparse representation for image restoration," IEEE Trans. Image Process. 23, 3336-3351 (2014).
    • (2014) IEEE Trans. Image Process. , vol.23 , pp. 3336-3351
    • Zhang, J.1    Zhao, D.2    Gao, W.3
  • 19
  • 20
    • 0033076357 scopus 로고    scopus 로고
    • Using evolutionary programming and minimum description length principle for data mining of Bayesian networks
    • M. L. Wong, W. Lam, and K. S. Leung, "Using evolutionary programming and minimum description length principle for data mining of Bayesian networks," IEEE Trans. Pattern Anal. Mach. Intell. 21, 174-178 (1999).
    • (1999) IEEE Trans. Pattern Anal. Mach. Intell. , vol.21 , pp. 174-178
    • Wong, M.L.1    Lam, W.2    Leung, K.S.3
  • 22
    • 33750383209 scopus 로고    scopus 로고
    • K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation
    • M. Aharon, M. Elad, and A. Bruckstein, "K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation," IEEE Trans. Signal Process. 54, 4311-4322 (2006).
    • (2006) IEEE Trans. Signal Process. , vol.54 , pp. 4311-4322
    • Aharon, M.1    Elad, M.2    Bruckstein, A.3
  • 23
    • 33751379736 scopus 로고    scopus 로고
    • Image denoising via sparse and redundant representations over learned dictionaries
    • M. Elad and M. Aharon, "Image denoising via sparse and redundant representations over learned dictionaries," IEEE Trans. Image Process. 15, 3736-3745 (2006).
    • (2006) IEEE Trans. Image Process. , vol.15 , pp. 3736-3745
    • Elad, M.1    Aharon, M.2
  • 24
    • 0000874557 scopus 로고
    • Theoretical foundations of the potential function method in pattern recognition learning
    • M. A. Aizerman, E. A. Braverman, and L. I. Rozonoer, "Theoretical foundations of the potential function method in pattern recognition learning," Automat. Remote Control 25, 821-837 (1964).
    • (1964) Automat. Remote Control , vol.25 , pp. 821-837
    • Aizerman, M.A.1    Braverman, E.A.2    Rozonoer, L.I.3
  • 25
    • 80053571096 scopus 로고    scopus 로고
    • Hyperspectral image classification using dictionary-based sparse representation
    • Y. Chen, N. M. Nasrabadi, and T. D. Tran, "Hyperspectral image classification using dictionary-based sparse representation," IEEE Trans. Geosci. Remote Sens. 49, 3973-3985 (2011).
    • (2011) IEEE Trans. Geosci. Remote Sens. , vol.49 , pp. 3973-3985
    • Chen, Y.1    Nasrabadi, N.M.2    Tran, T.D.3
  • 27
    • 64649083745 scopus 로고    scopus 로고
    • Signal recovery from random measurements via orthogonal matching pursuit
    • J. A. Tropp and A. C. Gilbert, "Signal recovery from random measurements via orthogonal matching pursuit," IEEE Trans. Inf. Theory 53, 4655-4666 (2007).
    • (2007) IEEE Trans. Inf. Theory , vol.53 , pp. 4655-4666
    • Tropp, J.A.1    Gilbert, A.C.2
  • 28
    • 20444432773 scopus 로고    scopus 로고
    • Kernel-based methods for hyperspectral image classification
    • C. Camps-Valls and L. Bruzzone, "Kernel-based methods for hyperspectral image classification," IEEE Trans. Geosci. Remote Sens. 43, 1351-1362 (2005).
    • (2005) IEEE Trans. Geosci. Remote Sens. , vol.43 , pp. 1351-1362
    • Camps-Valls, C.1    Bruzzone, L.2
  • 29
    • 84871731919 scopus 로고    scopus 로고
    • Hyperspectral image classification via Kernel sparse representation
    • Y. Chen, N. M. Nasrabadi, and T. D. Tran, "Hyperspectral image classification via Kernel sparse representation," IEEE Trans. Geosci. Remote Sens. 51, 217-231 (2013).
    • (2013) IEEE Trans. Geosci. Remote Sens. , vol.51 , pp. 217-231
    • Chen, Y.1    Nasrabadi, N.M.2    Tran, T.D.3
  • 30
    • 77955828051 scopus 로고    scopus 로고
    • Efficient particle filtering via sparse Kernel density estimation
    • A. Banerjee and P. Burlina, "Efficient particle filtering via sparse Kernel density estimation," IEEE Trans. Image Process. 19, 2480-2490 (2010).
    • (2010) IEEE Trans. Image Process. , vol.19 , pp. 2480-2490
    • Banerjee, A.1    Burlina, P.2
  • 31
    • 73949106180 scopus 로고    scopus 로고
    • Hyperspectral agricultural mapping using support vector machine-based endmember extraction (SVM-BEE)
    • A. M. Filippi, R. Archibald, B. L. Bhaduri, and E. A. Bright, "Hyperspectral agricultural mapping using support vector machine-based endmember extraction (SVM-BEE)," Opt. Express 17, 23823-23842 (2009).
    • (2009) Opt. Express , vol.17 , pp. 23823-23842
    • Filippi, A.M.1    Archibald, R.2    Bhaduri, B.L.3    Bright, E.A.4
  • 32
    • 84903278535 scopus 로고    scopus 로고
    • Spectralspartial hyperspectral image classification via multiscale adaptive sparse representation
    • L. Fang, S. Li, X. Kang, and J. A. Benediktsson, "Spectralspartial hyperspectral image classification via multiscale adaptive sparse representation," IEEE Trans. Geosci. Remote Sens. 52, 7738-7749 (2014).
    • (2014) IEEE Trans. Geosci. Remote Sens. , vol.52 , pp. 7738-7749
    • Fang, L.1    Li, S.2    Kang, X.3    Benediktsson, J.A.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.