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Volumn 124, Issue , 2016, Pages 184-197

A scene change detection framework for multi-temporal very high resolution remote sensing images

Author keywords

BOVW; Compound classification; Post classification; Remote sensing; Scene change detection; VHR image

Indexed keywords

COMPUTER VISION; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGE RECONSTRUCTION; LAND USE; OBJECT RECOGNITION; REMOTE SENSING; SEMANTICS; SIGNAL DETECTION;

EID: 84960296195     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2015.09.020     Document Type: Article
Times cited : (113)

References (41)
  • 1
  • 2
    • 85027924183 scopus 로고    scopus 로고
    • Multiview Hessian regularized logistic regression for action recognition
    • W.F. Liu, H.L. Liu, D.P. Tao, Y.J. Wang, and K. Lu Multiview Hessian regularized logistic regression for action recognition Signal Process. 110 2015 101 107
    • (2015) Signal Process. , vol.110 , pp. 101-107
    • Liu, W.F.1    Liu, H.L.2    Tao, D.P.3    Wang, Y.J.4    Lu, K.5
  • 4
    • 33746424489 scopus 로고    scopus 로고
    • Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval
    • D.C. Tao, X. Tang, X.L. Li, and X.D. Wu Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval IEEE Trans. Pattern Anal. Mach. Intell. 28 2006 1088 1099
    • (2006) IEEE Trans. Pattern Anal. Mach. Intell. , vol.28 , pp. 1088-1099
    • Tao, D.C.1    Tang, X.2    Li, X.L.3    Wu, X.D.4
  • 6
    • 84877887638 scopus 로고    scopus 로고
    • Multiview Hessian regularization for image annotation
    • L. Weifeng, and T. Dacheng Multiview Hessian regularization for image annotation Image Process. IEEE Trans. 22 2013 2676 2687
    • (2013) Image Process. IEEE Trans. , vol.22 , pp. 2676-2687
    • Weifeng, L.1    Dacheng, T.2
  • 7
    • 84890560521 scopus 로고    scopus 로고
    • Multiview Hessian discriminative sparse coding for image annotation
    • W. Liu, D. Tao, J. Cheng, and Y. Tang Multiview Hessian discriminative sparse coding for image annotation Comput. Vis. Image Underst. 118 1// 2014 50 60
    • (2014) Comput. Vis. Image Underst. , vol.118 , Issue.1 , pp. 50-60
    • Liu, W.1    Tao, D.2    Cheng, J.3    Tang, Y.4
  • 8
    • 84902073586 scopus 로고    scopus 로고
    • A discriminative metric learning based anomaly detection method
    • D. Bo, and Z. Liangpei A discriminative metric learning based anomaly detection method IEEE Trans. Geosci. Remote Sens. 52 2014 6844 6857
    • (2014) IEEE Trans. Geosci. Remote Sens. , vol.52 , pp. 6844-6857
    • Bo, D.1    Liangpei, Z.2
  • 9
    • 84882843009 scopus 로고    scopus 로고
    • Unsupervised transfer learning for target detection from hyperspectral images
    • B. Du, L. Zhang, D. Tao, and D. Zhang Unsupervised transfer learning for target detection from hyperspectral images Neurocomputing 120 2013 72 82
    • (2013) Neurocomputing , vol.120 , pp. 72-82
    • Du, B.1    Zhang, L.2    Tao, D.3    Zhang, D.4
  • 11
    • 0024855524 scopus 로고
    • Review Article Digital change detection techniques using remotely-sensed data
    • A. Singh Review Article Digital change detection techniques using remotely-sensed data Int. J. Remote Sens. 10 1989 989 1003
    • (1989) Int. J. Remote Sens. , vol.10 , pp. 989-1003
    • Singh, A.1
  • 12
    • 85027955883 scopus 로고    scopus 로고
    • A hypothesis independent subpixel target detector for hyperspectral Images
    • B. Du, Y. Zhang, L. Zhang, and L. Zhang A hypothesis independent subpixel target detector for hyperspectral Images Signal Process. 110 2015 244 249
    • (2015) Signal Process. , vol.110 , pp. 244-249
    • Du, B.1    Zhang, Y.2    Zhang, L.3    Zhang, L.4
  • 13
    • 84885022681 scopus 로고    scopus 로고
    • Target detection based on a dynamic subspace
    • B. Du, and L. Zhang Target detection based on a dynamic subspace Pattern Recognit. 47 2014 344 358
    • (2014) Pattern Recognit. , vol.47 , pp. 344-358
    • Du, B.1    Zhang, L.2
  • 14
    • 79955590723 scopus 로고    scopus 로고
    • Random-selection-based anomaly detector for hyperspectral imagery
    • B. Du, and L. Zhang Random-selection-based anomaly detector for hyperspectral imagery IEEE Trans. Geosci. Remote Sens. 49 2011 1578 1589
    • (2011) IEEE Trans. Geosci. Remote Sens. , vol.49 , pp. 1578-1589
    • Du, B.1    Zhang, L.2
  • 15
    • 67349132266 scopus 로고    scopus 로고
    • Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects
    • R.E. Kennedy, P.A. Townsend, J.E. Gross, W.B. Cohen, P. Bolstad, Y.Q. Wang, and P. Adams Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects Remote Sens. Environ. 113 2009 1382 1396
    • (2009) Remote Sens. Environ. , vol.113 , pp. 1382-1396
    • Kennedy, R.E.1    Townsend, P.A.2    Gross, J.E.3    Cohen, W.B.4    Bolstad, P.5    Wang, Y.Q.6    Adams, P.7
  • 16
    • 0030833148 scopus 로고    scopus 로고
    • Detection and analysis of change in remotely sensed imagery with application to wide area surveillance
    • M.J. Carlotto Detection and analysis of change in remotely sensed imagery with application to wide area surveillance IEEE Trans. Image Process. 6 1997 189 202
    • (1997) IEEE Trans. Image Process. , vol.6 , pp. 189-202
    • Carlotto, M.J.1
  • 18
    • 33846223394 scopus 로고    scopus 로고
    • A Theoretical Framework for Unsupervised Change Detection Based on Change Vector Analysis in the Polar Domain
    • F. Bovolo, and L. Bruzzone A Theoretical Framework for Unsupervised Change Detection Based on Change Vector Analysis in the Polar Domain IEEE Trans. Geosci. Remote Sens. 45 2007 218 236
    • (2007) IEEE Trans. Geosci. Remote Sens. , vol.45 , pp. 218-236
    • Bovolo, F.1    Bruzzone, L.2
  • 19
    • 84896317984 scopus 로고    scopus 로고
    • Slow feature analysis for change detection in multispectral imagery
    • C. Wu, B. Du, and L. Zhang Slow feature analysis for change detection in multispectral imagery IEEE Trans. Geosci. Remote Sens. 52 2014 2858 2874
    • (2014) IEEE Trans. Geosci. Remote Sens. , vol.52 , pp. 2858-2874
    • Wu, C.1    Du, B.2    Zhang, L.3
  • 20
    • 84860338492 scopus 로고    scopus 로고
    • Detection of land-cover transitions in multitemporal remote sensing images with active-learning-based compound classification.
    • B. Demir, F. Bovolo, and L. Bruzzone Detection of land-cover transitions in multitemporal remote sensing images with active-learning-based compound classification. IEEE Trans. Geosci. Remote Sens. 50 2012 1930 1941
    • (2012) IEEE Trans. Geosci. Remote Sens. , vol.50 , pp. 1930-1941
    • Demir, B.1    Bovolo, F.2    Bruzzone, L.3
  • 21
    • 64549085340 scopus 로고    scopus 로고
    • Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods
    • G. Xian, C. Homer, and J. Fry Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods Remote Sens. Environ. 113 2009 1133 1147
    • (2009) Remote Sens. Environ. , vol.113 , pp. 1133-1147
    • Xian, G.1    Homer, C.2    Fry, J.3
  • 22
    • 84876726723 scopus 로고    scopus 로고
    • Change detection from remotely sensed images: From pixel-based to object-based approaches
    • M. Hussain, D. Chen, A. Cheng, H. Wei, and D. Stanley Change detection from remotely sensed images: From pixel-based to object-based approaches ISPRS J. Photogramm. 80 2013 91 106
    • (2013) ISPRS J. Photogramm. , vol.80 , pp. 91-106
    • Hussain, M.1    Chen, D.2    Cheng, A.3    Wei, H.4    Stanley, D.5
  • 24
    • 33745858268 scopus 로고    scopus 로고
    • Scene Classification Via pLSA
    • A. Leonardis, et al. (Eds.) Springer Berlin Heidelberg
    • A. Bosch, A. Zisserman, and X. Muñoz Scene Classification Via pLSA A. Leonardis, et al. (Eds.) Computer Vision - ECCV 2006 3954 2006 Springer Berlin Heidelberg 517 530
    • (2006) Computer Vision - ECCV 2006 , vol.3954 , pp. 517-530
    • Bosch, A.1    Zisserman, A.2    Muñoz, X.3
  • 26
  • 27
    • 84890425279 scopus 로고    scopus 로고
    • Unsupervised feature learning for aerial scene classification
    • A.M. Cheriyadat Unsupervised feature learning for aerial scene classification IEEE Trans. Geosci. Remote Sens. 52 2014 439 451
    • (2014) IEEE Trans. Geosci. Remote Sens. , vol.52 , pp. 439-451
    • Cheriyadat, A.M.1
  • 28
    • 84870903062 scopus 로고    scopus 로고
    • Automatic Annotation of Satellite Images via Multifeature Joint Sparse Coding with Spatial Relation Constraint
    • X. Zheng, X. Sun, K. Fu, and H. Wang Automatic Annotation of Satellite Images via Multifeature Joint Sparse Coding With Spatial Relation Constraint IEEE Geosci. Remote Sens. Lett. 10 2013 652 656
    • (2013) IEEE Geosci. Remote Sens. Lett. , vol.10 , pp. 652-656
    • Zheng, X.1    Sun, X.2    Fu, K.3    Wang, H.4
  • 29
    • 84881242291 scopus 로고    scopus 로고
    • A hierarchical scheme of multiple feature fusion for high-resolution satellite scene categorization
    • M. Chen, et al. (Eds.) Springer Berlin Heidelberg
    • W. Shao, W. Yang, G.S. Xia, and G. Liu A hierarchical scheme of multiple feature fusion for high-resolution satellite scene categorization M. Chen, et al. (Eds.) Computer Vision Systems 7963 2013 Springer Berlin Heidelberg 324 333
    • (2013) Computer Vision Systems , vol.7963 , pp. 324-333
    • Shao, W.1    Yang, W.2    Xia, G.S.3    Liu, G.4
  • 31
    • 84863271556 scopus 로고    scopus 로고
    • High-resolution satellite scene classification using a sparse coding based multiple feature combination
    • G. Sheng, W. Yang, T. Xu, and H. Sun High-resolution satellite scene classification using a sparse coding based multiple feature combination Int. J. Remote Sens. 33 2011 2395 2412
    • (2011) Int. J. Remote Sens. , vol.33 , pp. 2395-2412
    • Sheng, G.1    Yang, W.2    Xu, T.3    Sun, H.4
  • 32
    • 84861198977 scopus 로고    scopus 로고
    • Automatic annotation of multispectral satellite images using author-topic model
    • L. Wang, L. Hongliang, and L. Guanghui Automatic annotation of multispectral satellite images using author-topic model IEEE Geosci. Remote Sens. Lett. 9 2012 634 638
    • (2012) IEEE Geosci. Remote Sens. Lett. , vol.9 , pp. 634-638
    • Wang, L.1    Hongliang, L.2    Guanghui, L.3
  • 33
    • 84890096359 scopus 로고    scopus 로고
    • Scene classification via latent Dirichlet allocation using a hybrid generative/discriminative strategy for high spatial resolution remote sensing imagery
    • B. Zhao, Y. Zhong, and L. Zhang Scene classification via latent Dirichlet allocation using a hybrid generative/discriminative strategy for high spatial resolution remote sensing imagery Remote Sens. Lett. 4 2013 1204 1213
    • (2013) Remote Sens. Lett. , vol.4 , pp. 1204-1213
    • Zhao, B.1    Zhong, Y.2    Zhang, L.3
  • 34
    • 75449091209 scopus 로고    scopus 로고
    • Semantic annotation of satellite images using latent dirichlet allocation
    • M. Lienou, H. Maitre, and M. Datcu Semantic annotation of satellite images using latent dirichlet allocation IEEE Geosci. Remote Sens. Lett. 7 2010 28 32
    • (2010) IEEE Geosci. Remote Sens. Lett. , vol.7 , pp. 28-32
    • Lienou, M.1    Maitre, H.2    Datcu, M.3
  • 36
    • 84877754121 scopus 로고    scopus 로고
    • Scale invariant feature transform
    • T. Lindeberg Scale invariant feature transform Scholarpedia, 7 2012 10491
    • (2012) Scholarpedia , vol.7
    • Lindeberg, T.1
  • 38
    • 84872575253 scopus 로고    scopus 로고
    • Learning feature representations with k-means
    • S.S. Haykin, M. Grégoire, B.O. Geneviève, M. Klaus-Robert (Eds.), Springer Heidelberg
    • A. Coates, and A.Y. Ng Learning feature representations with k-means S.S. Haykin, M. Grégoire, B.O. Geneviève, M. Klaus-Robert (Eds.), Neural Networks: Tricks of the Trade 2012 Springer Heidelberg 561 580
    • (2012) Neural Networks: Tricks of the Trade , pp. 561-580
    • Coates, A.1    Ng, A.Y.2
  • 39
    • 80052087210 scopus 로고    scopus 로고
    • On combining multiple features for hyperspectral remote sensing image classification
    • L. Zhang, L. Zhang, D. Tao, and X. Huang On combining multiple features for hyperspectral remote sensing image classification IEEE Trans. Geosci. Remote Sens. 50 2012 879 893
    • (2012) IEEE Trans. Geosci. Remote Sens. , vol.50 , pp. 879-893
    • Zhang, L.1    Zhang, L.2    Tao, D.3    Huang, X.4
  • 41
    • 84862227138 scopus 로고    scopus 로고
    • An automated approach for updating land cover maps based on integrated change detection and classification methods
    • X. Chen, J. Chen, Y. Shi, and Y. Yamaguchi An automated approach for updating land cover maps based on integrated change detection and classification methods ISPRS J. Photogramm. 71 2012 86 95
    • (2012) ISPRS J. Photogramm. , vol.71 , pp. 86-95
    • Chen, X.1    Chen, J.2    Shi, Y.3    Yamaguchi, Y.4


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