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Volumn 7872 LNCS, Issue , 2013, Pages 343-351

MRF-based multiple classifier system for hyperspectral remote sensing image classification

Author keywords

[No Author keywords available]

Indexed keywords

AIRBORNE VISIBLE INFRARED IMAGING SPECTROMETER; CLASSIFICATION RESULTS; GENERALIZATION CAPACITY; HYPERSPECTRAL IMAGE CLASSIFICATION; HYPERSPECTRAL REMOTE SENSING IMAGE; MULTINOMIAL LOGISTIC REGRESSION; MULTIPLE CLASSIFIER SYSTEMS; SUPERVISED CLASSIFIERS;

EID: 84892935834     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-38067-9_30     Document Type: Conference Paper
Times cited : (7)

References (19)
  • 1
    • 37249003229 scopus 로고    scopus 로고
    • Multiple classifier systems in remote sensing: From basics to recent developments
    • Haindl, M., Kittler, J., Roli, F. (eds.) MCS 2007. Springer, Heidelberg
    • Benediktsson, J.A., Chanussot, J., Fauvel, M.: Multiple classifier systems in remote sensing: from basics to recent developments. In: Haindl, M., Kittler, J., Roli, F. (eds.) MCS 2007. LNCS, vol. 4472, pp. 501-512. Springer, Heidelberg (2007)
    • (2007) LNCS , vol.4472 , pp. 501-512
    • Benediktsson, J.A.1    Chanussot, J.2    Fauvel, M.3
  • 2
    • 43949125818 scopus 로고    scopus 로고
    • Evaluation of Random Forest and Adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery
    • Chan, J.C., Paelinckx, D.: Evaluation of Random Forest and Adaboost tree-based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery. Remote Sens. Environ. 112, 2999-3011 (2008)
    • (2008) Remote Sens. Environ. , vol.112 , pp. 2999-3011
    • Chan, J.C.1    Paelinckx, D.2
  • 4
    • 84860267020 scopus 로고    scopus 로고
    • Multiple Classifier System for Remote Sensing Image Classification: A Review
    • Du, P., Xia, J., Zhang, W., Tan, K., Liu, Y., Liu, S.: Multiple Classifier System for Remote Sensing Image Classification: A Review. Sensors 12, 4764-4792 (2012)
    • (2012) Sensors , vol.12 , pp. 4764-4792
    • Du, P.1    Xia, J.2    Zhang, W.3    Tan, K.4    Liu, Y.5    Liu, S.6
  • 7
    • 34547111054 scopus 로고    scopus 로고
    • Mapping a specific class with an ensemble of classifiers
    • Foody, G.M., Boyd, D.S., Sanchez-Hernandez, C.: Mapping a specific class with an ensemble of classifiers. Int. J. Remote Sens. 28, 1733-1746 (2007)
    • (2007) Int. J. Remote Sens. , vol.28 , pp. 1733-1746
    • Foody, G.M.1    Boyd, D.S.2    Sanchez-Hernandez, C.3
  • 8
    • 34748885521 scopus 로고    scopus 로고
    • Increasing soft classification accuracy through the use of an ensemble of classifiers
    • Doan, H.T.X., Foody, G.M.: Increasing soft classification accuracy through the use of an ensemble of classifiers. Int. J. Remote Sens. 28, 4609-4623 (2007)
    • (2007) Int. J. Remote Sens. , vol.28 , pp. 4609-4623
    • Doan, H.T.X.1    Foody, G.M.2
  • 9
    • 84867399355 scopus 로고    scopus 로고
    • Classification of hyperspectral images by tensor modeling and additive morphological decomposition
    • Velasco-Forero, S., Angulo, J.: Classification of hyperspectral images by tensor modeling and additive morphological decomposition. Pattern Recogn. 46, 566-577 (2012)
    • (2012) Pattern Recogn. , vol.46 , pp. 566-577
    • Velasco-Forero, S.1    Angulo, J.2
  • 11
    • 23844524154 scopus 로고    scopus 로고
    • A unified framework for map estimation in remote sensing image segmentation
    • Farag, A., Mohamed, R., El-Baz, A.: A unified framework for map estimation in remote sensing image segmentation. IEEE Trans. Geosci. Remote Sens. 43, 1617-1634 (2005)
    • (2005) IEEE Trans. Geosci. Remote Sens. , vol.43 , pp. 1617-1634
    • Farag, A.1    Mohamed, R.2    El-Baz, A.3
  • 12
    • 33644753678 scopus 로고    scopus 로고
    • A spatial-temporal approach to monitoring forest disease spread using multi-temporal high spatial resolution imagery
    • Liu, D., Kelly, M., Gong, P.: A spatial-temporal approach to monitoring forest disease spread using multi-temporal high spatial resolution imagery. Remote Sens. Environ. 101, 167-180 (2006)
    • (2006) Remote Sens. Environ. , vol.101 , pp. 167-180
    • Liu, D.1    Kelly, M.2    Gong, P.3
  • 14
    • 80053562930 scopus 로고    scopus 로고
    • Hyperspectral Image Segmentation Using a New Bayesian Approach with Active Learning
    • Li, J., Bioucas-Dias, J.M., Plaza, A.: Hyperspectral Image Segmentation Using a New Bayesian Approach with Active Learning. IEEE Trans. Geosci. Remote Sens. 49, 3947-3960 (2011)
    • (2011) IEEE Trans. Geosci. Remote Sens. , vol.49 , pp. 3947-3960
    • Li, J.1    Bioucas-Dias, J.M.2    Plaza, A.3
  • 15
    • 0035420134 scopus 로고    scopus 로고
    • Design of effective neural network ensembles for image classification
    • Giacinto, G., Roli, F.: Design of effective neural network ensembles for image classification. Image Vis. Comput. J. 19, 697-705 (2001)
    • (2001) Image Vis. Comput. J. , vol.19 , pp. 697-705
    • Giacinto, G.1    Roli, F.2
  • 16
    • 84872950801 scopus 로고    scopus 로고
    • A Graph-Based Classification Method for Hyperspectral Images
    • Bai, J., Xiang, S., Pan, C.: A Graph-Based Classification Method for Hyperspectral Images. IEEE Trans. Geosci. Remote Sens. 803-816, 2113-2118 (2013)
    • (2013) IEEE Trans. Geosci. Remote Sens. , vol.803-816 , pp. 2113-2118
    • Bai, J.1    Xiang, S.2    Pan, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.