메뉴 건너뛰기




Volumn 9, Issue 10, 2017, Pages

Band selection-based dimensionality reduction for change detection in multi-temporal hyperspectral images

Author keywords

Band selection; Change detection (CD); Dimensionality reduction; Hyperspectral images; Multi temporal images; Remote sensing

Indexed keywords

CLUSTERING ALGORITHMS; COMPUTATIONAL EFFICIENCY; HYPERSPECTRAL IMAGING; REMOTE SENSING;

EID: 85032871062     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs9101008     Document Type: Article
Times cited : (48)

References (47)
  • 1
    • 84906782734 scopus 로고    scopus 로고
    • Hierarchical change detection in multitemporal hyperspectral images
    • Liu, S.; Bruzzone, L.; Bovolo, F.; Du, P. Hierarchical change detection in multitemporal hyperspectral images. IEEE Trans. Geosci. Remote Sens. 2015, 53, 244-260.
    • (2015) IEEE Trans. Geosci. Remote Sens , vol.53 , pp. 244-260
    • Liu, S.1    Bruzzone, L.2    Bovolo, F.3    Du, P.4
  • 2
    • 77957741951 scopus 로고
    • On the mean accuracy of statistical pattern recognizers
    • Hughes, G.F. On the mean accuracy of statistical pattern recognizers. IEEE Trans. Inf. Theory 1968, 14, 55-63.
    • (1968) IEEE Trans. Inf. Theory , vol.14 , pp. 55-63
    • Hughes, G.F.1
  • 3
    • 84929616566 scopus 로고    scopus 로고
    • Dimensionality reduction of hyperspectral images based on sparse discriminant manifold embedding
    • Huang, H.; Luo, F.; Liu, J.; Yang, Y. Dimensionality reduction of hyperspectral images based on sparse discriminant manifold embedding. ISPRS J. Photogramm. 2016, 106, 42-54.
    • (2016) ISPRS J. Photogramm , vol.106 , pp. 42-54
    • Huang, H.1    Luo, F.2    Liu, J.3    Yang, Y.4
  • 4
    • 84891584609 scopus 로고    scopus 로고
    • Hyperspectral Data Processing: Algorithm Design and Analysis?
    • Inc.: Hoboken, NJ, USA
    • Change, C.-I. Hyperspectral Data Processing: Algorithm Design and Analysis; John Wiley & Sons, Inc.: Hoboken, NJ, USA, 2013; pp. 168-198.
    • (2013) John Wiley & Sons , pp. 168-198
    • Change, C.-I.1
  • 6
    • 84899875503 scopus 로고    scopus 로고
    • Novel folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing
    • Zabalza, J.; Rem, J.; Yang, M.; Zhang, Y.;Wang, J.; Marshall, S.; Han, J. Novel folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing. ISPRS J. Photogramm. 2014, 93, 112-122.
    • (2014) ISPRS J. Photogramm , vol.93 , pp. 112-122
    • Zabalza, J.1    Rem, J.2    Yang, M.3    Zhang, Y.4    Wang, J.5    Marshall, S.6    Han, J.7
  • 8
    • 33744719449 scopus 로고    scopus 로고
    • Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis
    • Wang, J.; Chang, C.-I. Independent component analysis-based dimensionality reduction with applications in hyperspectral image analysis. IEEE Trans. Geosci. Remote Sens. 2006, 44, 1586-1600.
    • (2006) IEEE Trans. Geosci. Remote Sens , vol.44 , pp. 1586-1600
    • Wang, J.1    Chang, C.-I.2
  • 9
    • 0028467206 scopus 로고
    • Hyperspectral image classification and dimensionality reduction: An orthogonal subspace projection approach
    • Harsanyi, J.C.; Chang, C.-I. Hyperspectral image classification and dimensionality reduction: An orthogonal subspace projection approach. IEEE Trans. Geosci. Remote Sens. 1994, 32, 779-785.
    • (1994) IEEE Trans. Geosci. Remote Sens , vol.32 , pp. 779-785
    • Harsanyi, J.C.1    Chang, C.-I.2
  • 10
    • 55649124564 scopus 로고    scopus 로고
    • Similarity-based unsupervised band selection for hyperspectral image analysis
    • Du, Q.; Yang, H. Similarity-based unsupervised band selection for hyperspectral image analysis. IEEE Geosci. Remote Sens. Lett. 2008, 5, 564-568.
    • (2008) IEEE Geosci. Remote Sens. Lett , vol.5 , pp. 564-568
    • Du, Q.1    Yang, H.2
  • 11
    • 78650930212 scopus 로고    scopus 로고
    • An efficient method for supervised hyperspectral band selection
    • Yang, H.; Du, Q.; Su, H.; Sheng, Y. An efficient method for supervised hyperspectral band selection. IEEE Geosci. Remote Sens. Lett. 2011, 8, 138-142.
    • (2011) IEEE Geosci. Remote Sens. Lett , vol.8 , pp. 138-142
    • Yang, H.1    Du, Q.2    Su, H.3    Sheng, Y.4
  • 12
    • 84879931142 scopus 로고    scopus 로고
    • A feature-metric-based affinity propagation technique for feature selection in hyperspectralimage classification
    • Yang, C.; Liu, S.; Bruzzone, L.; Guan, R. A feature-metric-based affinity propagation technique for feature selection in hyperspectralimage classification. IEEE Geosci. Remote Sens. Lett. 2013, 10, 1152-1156.
    • (2013) IEEE Geosci. Remote Sens. Lett , vol.10 , pp. 1152-1156
    • Yang, C.1    Liu, S.2    Bruzzone, L.3    Guan, R.4
  • 14
    • 84947033565 scopus 로고    scopus 로고
    • A novel ranking-based clustering approach for hyperspectral band selection
    • Jia, S.; Tang, G.; Zhu, J.; Li, Q. A novel ranking-based clustering approach for hyperspectral band selection. IEEE Trans. Geosci. Remote Sens. 2016, 54, 88-102.
    • (2016) IEEE Trans. Geosci. Remote Sens , vol.54 , pp. 88-102
    • Jia, S.1    Tang, G.2    Zhu, J.3    Li, Q.4
  • 15
    • 84906307287 scopus 로고    scopus 로고
    • Hyperspectral band selection by multitask sparsity pursuit
    • Yuan, Y.; Zhu, G.;Wang, Q. Hyperspectral band selection by multitask sparsity pursuit. IEEE Trans. Geosci. Remote Sens. 2014, 53, 631-644.
    • (2014) IEEE Trans. Geosci. Remote Sens , vol.53 , pp. 631-644
    • Yuan, Y.1    Zhu, G.2    Wang, Q.3
  • 16
    • 84977998287 scopus 로고    scopus 로고
    • Salient band selection for hyperspectral image classification via manifold ranking
    • Wang, Q.; Lin, J.; Yuan, Y. Salient band selection for hyperspectral image classification via manifold ranking. IEEE Trans. Neural Netw. Learn. Syst. 2017, 27, 1279-1289.
    • (2017) IEEE Trans. Neural Netw. Learn. Syst , vol.27 , pp. 1279-1289
    • Wang, Q.1    Lin, J.2    Yuan, Y.3
  • 17
    • 84890560521 scopus 로고    scopus 로고
    • Multiview Hessian discriminative sparse coding for image annotation
    • Liu,W.; Tao, D.; Cheng, J.; Tang, Y. Multiview Hessian discriminative sparse coding for image annotation. Comput. Vis. Image Underst. 2014, 118, 50-60.
    • (2014) Comput. Vis. Image Underst , vol.118 , pp. 50-60
    • Liu, W.1    Tao, D.2    Cheng, J.3    Tang, Y.4
  • 18
    • 84973107222 scopus 로고    scopus 로고
    • p-Laplacian regularized sparse coding for human activity recognition
    • Liu, W.; Zha, Z.; Wang, Y.; Lu, K.; Tao, D. p-Laplacian regularized sparse coding for human activity recognition. IEEE Trans. Ind. Electron. 2016, 63, 5120-5129.
    • (2016) IEEE Trans. Ind. Electron , vol.63 , pp. 5120-5129
    • Liu, W.1    Zha, Z.2    Wang, Y.3    Lu, K.4    Tao, D.5
  • 20
    • 84874545870 scopus 로고    scopus 로고
    • A novel framework for the design of change-detection systems for very-high-resolution remote sensing images
    • Bruzzone, L.; Bovolo, F. A novel framework for the design of change-detection systems for very-high-resolution remote sensing images. Proc. IEEE 2013, 101, 609-630.
    • (2013) Proc. IEEE , vol.101 , pp. 609-630
    • Bruzzone, L.1    Bovolo, F.2
  • 21
    • 33846223394 scopus 로고    scopus 로고
    • A theoretical framework for unsupervised change detection based on change vector analysis in the polar domain
    • Bovolo, F.; Bruzzone, L. A theoretical framework for unsupervised change detection based on change vector analysis in the polar domain. IEEE Trans. Geosci. Remote Sens. 2007, 45, 218-236.
    • (2007) IEEE Trans. Geosci. Remote Sens , vol.45 , pp. 218-236
    • Bovolo, F.1    Bruzzone, L.2
  • 22
    • 84861340870 scopus 로고    scopus 로고
    • A framework for automatic and unsupervised detection of multiple changes in multitemporal images
    • Bovolo, F.; Marchesi, S.; Bruzzone, L. A framework for automatic and unsupervised detection of multiple changes in multitemporal images. IEEE Trans. Geosci. Remote Sens. 2012, 50, 2196-2212.
    • (2012) IEEE Trans. Geosci. Remote Sens , vol.50 , pp. 2196-2212
    • Bovolo, F.1    Marchesi, S.2    Bruzzone, L.3
  • 24
    • 84862227138 scopus 로고    scopus 로고
    • An automated approach for updating land cover maps based on integrated change detection and classification methods
    • Chen, X.; Chen, J.; Shi, Y.; Yamaguchi, Y. An automated approach for updating land cover maps based on integrated change detection and classification methods. ISPRS J. Photogramm. 2012, 71, 86-95.
    • (2012) ISPRS J. Photogramm , vol.71 , pp. 86-95
    • Chen, X.1    Chen, J.2    Shi, Y.3    Yamaguchi, Y.4
  • 25
    • 85019844317 scopus 로고    scopus 로고
    • Unsupervised change detection for multispectral remote sensing images using random walks
    • Liu, Q.; Liu, L.; Wang, Y. Unsupervised change detection for multispectral remote sensing images using random walks. Remote Sens. 2017, 9, 438.
    • (2017) Remote Sens , vol.9 , pp. 438
    • Liu, Q.1    Liu, L.2    Wang, Y.3
  • 26
    • 84883409373 scopus 로고    scopus 로고
    • A spectral gradient difference based approach for land cover change detection
    • Chen, J.; Lu, M.; Chen, X.; Chen, J.; Chen, L. A spectral gradient difference based approach for land cover change detection. ISPRS J. Photogramm. 2013, 85, 1-12.
    • (2013) ISPRS J. Photogramm , vol.85 , pp. 1-12
    • Chen, J.1    Lu, M.2    Chen, X.3    Chen, J.4    Chen, L.5
  • 27
    • 85019344774 scopus 로고    scopus 로고
    • Urban change analysis with multi-sensor multispectral imagery
    • Tang, Y.; Zhang, L. Urban change analysis with multi-sensor multispectral imagery. Remote Sens. 2017, 9, 252.
    • (2017) Remote Sens , vol.9 , pp. 252
    • Tang, Y.1    Zhang, L.2
  • 28
    • 84978953910 scopus 로고    scopus 로고
    • Change detection of built-up land: A framework of combining pixel-based detection and object-based recognition
    • Xiao, P.; Zhang, X.; Wang, D.; Yuan, M.; Feng, X.; Kelly, M. Change detection of built-up land: A framework of combining pixel-based detection and object-based recognition. ISPRS J. Photogramm. 2016, 119, 402-414.
    • (2016) ISPRS J. Photogramm , vol.119 , pp. 402-414
    • Xiao, P.1    Zhang, X.2    Wang, D.3    Yuan, M.4    Feng, X.5    Kelly, M.6
  • 31
    • 10444268146 scopus 로고    scopus 로고
    • Hyperspectral change detection and supervised matched filtering based on covariance equalization
    • Schaum, A.; Stocker, A. Hyperspectral change detection and supervised matched filtering based on covariance equalization. Proc. SPIE 2004, 5425, 77-90.
    • (2004) Proc. SPIE , vol.5425 , pp. 77-90
    • Schaum, A.1    Stocker, A.2
  • 33
    • 33748657175 scopus 로고    scopus 로고
    • Change detection in hyperspectral imagery using temporal principal components
    • Ortiz-Rivera, V.; Vélez-Reyes, M.; Roysam, B. Change detection in hyperspectral imagery using temporal principal components. Proc. SPIE 2006, 6233, 623312.
    • (2006) Proc. SPIE , vol.6233
    • Ortiz-Rivera, V.1    Vélez-Reyes, M.2    Roysam, B.3
  • 36
  • 37
    • 85027926154 scopus 로고    scopus 로고
    • Sequential spectral change vector analysis for iteratively discovering and detecting multiple changes in hyperspectral images
    • Liu, S.; Bruzzone, L.; Bovolo, F.; Zanetti, M.; Du, P. Sequential spectral change vector analysis for iteratively discovering and detecting multiple changes in hyperspectral images. IEEE Trans. Geosci. Remote Sens. 2015, 53, 4363-4378.
    • (2015) IEEE Trans. Geosci. Remote Sens , vol.53 , pp. 4363-4378
    • Liu, S.1    Bruzzone, L.2    Bovolo, F.3    Zanetti, M.4    Du, P.5
  • 38
    • 84954100585 scopus 로고    scopus 로고
    • Unsupervised multitemporal spectral unmixing for detecting multiple changes in hyperspectral images
    • Liu, S.; Bruzzone, L.; Bovolo, F.; Du, P. Unsupervised multitemporal spectral unmixing for detecting multiple changes in hyperspectral images. IEEE Trans. Geosci. Remote Sens. 2016, 54, 2733-2748.
    • (2016) IEEE Trans. Geosci. Remote Sens , vol.54 , pp. 2733-2748
    • Liu, S.1    Bruzzone, L.2    Bovolo, F.3    Du, P.4
  • 39
    • 3843151477 scopus 로고    scopus 로고
    • Distance metrics and band selection in hyperspectral processing with applications to material identification and spectral libraries
    • Keshava, N. Distance metrics and band selection in hyperspectral processing with applications to material identification and spectral libraries. IEEE Trans. Geosci. Remote Sens. 2004, 42, 1552-1565.
    • (2004) IEEE Trans. Geosci. Remote Sens , vol.42 , pp. 1552-1565
    • Keshava, N.1
  • 40
    • 0033707763 scopus 로고    scopus 로고
    • Automatic analysis of the difference image for unsupervised change detection
    • Bruzzone, L.; Prieto, D.F. Automatic analysis of the difference image for unsupervised change detection. IEEE Trans. Geosci. Remote Sens. 2000, 38, 1170-1182.
    • (2000) IEEE Trans. Geosci. Remote Sens , vol.38 , pp. 1170-1182
    • Bruzzone, L.1    Prieto, D.F.2
  • 41
    • 85011298923 scopus 로고    scopus 로고
    • Oil spill detection via multitemporal optical remote sensing images: A change detection perspective
    • Liu, S.; Chi, M.; Zou, Y.; Samat, A.; Benediktsson, J.A.; Plaza, A. Oil spill detection via multitemporal optical remote sensing images: A change detection perspective. IEEE Geosci. Remote Sens. Lett. 2017, 14, 324-328.
    • (2017) IEEE Geosci. Remote Sens. Lett , vol.14 , pp. 324-328
    • Liu, S.1    Chi, M.2    Zou, Y.3    Samat, A.4    Benediktsson, J.A.5    Plaza, A.6
  • 42
    • 84859388682 scopus 로고    scopus 로고
    • Land cover change detection over mining areas based on support vector machine
    • Du, P.; Liu, S.; Zheng, H. Land cover change detection over mining areas based on support vector machine. J. China Univ. Min. Technol. 2012, 41, 262-267.
    • (2012) J. China Univ. Min. Technol , vol.41 , pp. 262-267
    • Du, P.1    Liu, S.2    Zheng, H.3
  • 43
    • 84927582865 scopus 로고    scopus 로고
    • Random forest and rotation forest for fully polarized SAR image classification using polarimetric and spatial features
    • Du, P.; Samat, A.;Waske, B.; Liu, S.; Li, Z. Random forest and rotation forest for fully polarized SAR image classification using polarimetric and spatial features. ISPRS J. Photogramm. 2015, 105, 38-53.
    • (2015) ISPRS J. Photogramm , vol.105 , pp. 38-53
    • Du, P.1    Samat, A.2    Waske, B.3    Liu, S.4    Li, Z.5
  • 44
    • 79955702502 scopus 로고    scopus 로고
    • LIBSVM: A library for support vector machines
    • Chang, C.C.; Lin, C.J. LIBSVM: A library for support vector machines. ACM Trans. Intel. Syst. Technol. 2011, 2, 27:1-27:27.
    • (2011) ACM Trans. Intel. Syst. Technol , vol.2 , pp. 1-27
    • Chang, C.C.1    Lin, C.J.2
  • 45
    • 1842481516 scopus 로고    scopus 로고
    • Estimation of number of spectrally distinct signal sources in hyperspectral imagery
    • Chang, C.; Du, Q. Estimation of number of spectrally distinct signal sources in hyperspectral imagery. IEEE Trans. Geosci. Remote Sens. 2004, 42, 608-619.
    • (2004) IEEE Trans. Geosci. Remote Sens , vol.42 , pp. 608-619
    • Chang, C.1    Du, Q.2
  • 46
    • 84866234414 scopus 로고    scopus 로고
    • Empirical automatic estimation of the number of endmembers in hyperspectral images
    • Luo, B.; Chanussot, J.; Doute, S.; Zhang, L. Empirical automatic estimation of the number of endmembers in hyperspectral images. IEEE Geosci. Remote Sens. Lett. 2013, 10, 24-28.
    • (2013) IEEE Geosci. Remote Sens. Lett , vol.10 , pp. 24-28
    • Luo, B.1    Chanussot, J.2    Doute, S.3    Zhang, L.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.