메뉴 건너뛰기




Volumn 11, Issue 11, 2014, Pages 1986-1990

Feature extraction using attraction points for classification of hyperspectral images in a small sample size situation

Author keywords

Attraction points; feature extraction (FE); hyperspectral image; limited training sample

Indexed keywords

FACE RECOGNITION; FEATURE EXTRACTION; SAMPLING; SPECTROSCOPY;

EID: 84901835234     PISSN: 1545598X     EISSN: None     Source Type: Journal    
DOI: 10.1109/LGRS.2014.2316134     Document Type: Article
Times cited : (45)

References (22)
  • 1
    • 77957741951 scopus 로고
    • On the mean accuracy of statistical pattern recognition
    • Jan.
    • G. F. Hughes, "On the mean accuracy of statistical pattern recognition," IEEE Trans. Inf. Theory, vol. IT-14, no. 1, pp. 55-63, Jan. 1968.
    • (1968) IEEE Trans. Inf. Theory , vol.IT-14 , Issue.1 , pp. 55-63
    • Hughes, G.F.1
  • 2
    • 77957990796 scopus 로고    scopus 로고
    • An effective feature selection method for hyperspectral image classification based on genetic algorithm and support vector machine
    • Feb.
    • S. Li, H. Wu, D. Wan, and J. Zhu, "An effective feature selection method for hyperspectral image classification based on genetic algorithm and support vector machine," Knowl.-Based Syst., vol. 24, no. 1, pp. 40-48, Feb. 2011.
    • (2011) Knowl.-Based Syst. , vol.24 , Issue.1 , pp. 40-48
    • Li, S.1    Wu, H.2    Wan, D.3    Zhu, J.4
  • 3
    • 24344458137 scopus 로고    scopus 로고
    • Feature selection based on mutual information: Criteria of Max-Dependency, Max-Relevance, and Min-Redundancy
    • DOI 10.1109/TPAMI.2005.159
    • H. Peng, F. Long, and C. Ding, "Feature selection based on mutual information: Criteria of max dependency, max-relevance, and minredundancy," IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 8, pp. 1226-1238, Aug. 2005. (Pubitemid 41245053)
    • (2005) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.27 , Issue.8 , pp. 1226-1238
    • Peng, H.1    Long, F.2    Ding, C.3
  • 4
    • 84867975740 scopus 로고    scopus 로고
    • A new dimensionality reduction algorithm for hyperspectral image data using evolutionary strategy
    • Nov.
    • J. Yin, Y. Wang, and J. Hu, "A new dimensionality reduction algorithm for hyperspectral image data using evolutionary strategy," IEEE Trans. Ind. Inf., vol. 8, no. 4, pp. 935-943, Nov. 2012.
    • (2012) IEEE Trans. Ind. Inf. , vol.8 , Issue.4 , pp. 935-943
    • Yin, J.1    Wang, Y.2    Hu, J.3
  • 5
    • 70349332954 scopus 로고    scopus 로고
    • A novel approach to the selection of spatially invariant features for the classification of hyperspectral images with improved generalization capability
    • Sep.
    • L. Bruzzone and C. Persello, "A novel approach to the selection of spatially invariant features for the classification of hyperspectral images with improved generalization capability," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 9, pp. 3180-3191, Sep. 2009.
    • (2009) IEEE Trans. Geosci. Remote Sens. , vol.47 , Issue.9 , pp. 3180-3191
    • Bruzzone, L.1    Persello, C.2
  • 6
    • 84861725237 scopus 로고    scopus 로고
    • A quantitative and comparative assessment of unmixing-based feature extraction techniques for hyperspectral image classification
    • Apr.
    • I. Dópido, A. Villa, A. Plaza, and P. Gamba, "A quantitative and comparative assessment of unmixing-based feature extraction techniques for hyperspectral image classification," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 5, no. 2, pp. 421-435, Apr. 2012.
    • (2012) IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. , vol.5 , Issue.2 , pp. 421-435
    • Dópido, I.1    Villa, A.2    Plaza, A.3    Gamba, P.4
  • 7
    • 84897841949 scopus 로고    scopus 로고
    • Band clustering-based feature extraction for classification of hyperspectral images using limited training samples
    • Aug.
    • M. Imani and H. Ghassemian, "Band clustering-based feature extraction for classification of hyperspectral images using limited training samples," IEEE Geosci. Remote Sens. Lett., vol. 11, no. 8, pp. 1325-1329, Aug. 2014.
    • (2014) IEEE Geosci. Remote Sens. Lett. , vol.11 , Issue.8 , pp. 1325-1329
    • Imani, M.1    Ghassemian, H.2
  • 8
    • 84877926149 scopus 로고    scopus 로고
    • Neighborhood preserving orthogonal PNMF feature extraction for hyperspectral image classification
    • Apr.
    • J. Wen, Z. Tian, and X. Liu, "Neighborhood preserving orthogonal PNMF feature extraction for hyperspectral image classification," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 6, no. 2, pp. 759-768, Apr. 2013.
    • (2013) IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens. , vol.6 , Issue.2 , pp. 759-768
    • Wen, J.1    Tian, Z.2    Liu, X.3
  • 9
    • 42549151882 scopus 로고    scopus 로고
    • Relevance-based feature extraction for hyperspectral images
    • DOI 10.1109/TNN.2007.914156
    • M. J. Mendenhall and E. Merényi, "Relevance-based feature extraction for hyperspectral images," IEEE Trans. Neural Netw., vol. 19, no. 4, pp. 658-672, Apr. 2008. (Pubitemid 351583581)
    • (2008) IEEE Transactions on Neural Networks , vol.19 , Issue.4 , pp. 658-672
    • Mendenhall, M.J.1    Merenyi, E.2
  • 10
    • 84870934678 scopus 로고    scopus 로고
    • Linear feature extraction for hyperspectral images based on information theoretic learning
    • Jun.
    • M. Kamandar and H. Ghassemian, "Linear feature extraction for hyperspectral images based on information theoretic learning," IEEE Geosci. Remote Sens. Lett., vol. 10, no. 4, pp. 702-706, Jun. 2013.
    • (2013) IEEE Geosci. Remote Sens. Lett. , vol.10 , Issue.4 , pp. 702-706
    • Kamandar, M.1    Ghassemian, H.2
  • 11
    • 84874545698 scopus 로고    scopus 로고
    • Feature mining for hyperspectral image classification
    • Mar.
    • X. Jia, B. C. Kuo, and M. Crawford, "Feature mining for hyperspectral image classification," Proc. IEEE, vol. 101, no. 3, pp. 676-697, Mar. 2013.
    • (2013) Proc. IEEE , vol.101 , Issue.3 , pp. 676-697
    • Jia, X.1    Kuo, B.C.2    Crawford, M.3
  • 12
    • 84871993453 scopus 로고    scopus 로고
    • Semisupervised local discriminant analysis for feature extraction in hyperspectral images
    • Jan.
    • W. Liao, A. Piurica, P. Scheunders, W. Philips, and Y. Pi, "Semisupervised local discriminant analysis for feature extraction in hyperspectral images," IEEE Trans. Geosci. Remote Sens., vol. 51, no. 1, pp. 184-198, Jan. 2013.
    • (2013) IEEE Trans. Geosci. Remote Sens. , vol.51 , Issue.1 , pp. 184-198
    • Liao, W.1    Piurica, A.2    Scheunders, P.3    Philips, W.4    Pi, Y.5
  • 13
    • 84861192230 scopus 로고    scopus 로고
    • Using Hurst and Lyapunov exponent for hyperspectral image feature extraction
    • Jul.
    • J. Yin, C. Gao, and X. Jia, "Using Hurst and Lyapunov exponent for hyperspectral image feature extraction," IEEE Geosci. Remote Sens. Lett., vol. 9, no. 4, pp. 705-709, Jul. 2012.
    • (2012) IEEE Geosci. Remote Sens. Lett. , vol.9 , Issue.4 , pp. 705-709
    • Yin, J.1    Gao, C.2    Jia, X.3
  • 14
    • 33846625519 scopus 로고    scopus 로고
    • Feature extraction in remote sensing high-dimensional image data
    • DOI 10.1109/LGRS.2006.886429
    • M. Zortea, V. Haertel, and R. Clarke, "Feature extraction in remote sensing high-dimensional image data," IEEE Geosci. Remote Sens. Lett., vol. 4, no. 1, pp. 107-111, Jan. 2007. (Pubitemid 46180266)
    • (2007) IEEE Geoscience and Remote Sensing Letters , vol.4 , Issue.1 , pp. 107-111
    • Zortea, M.1    Haertel, V.2    Clarke, R.3
  • 15
    • 84870859089 scopus 로고    scopus 로고
    • Wavelet packet analysis and gray model for feature extraction of hyperspectral data
    • Jul.
    • J. Yin, C. Gao, and X. Jia, "Wavelet packet analysis and gray model for feature extraction of hyperspectral data," IEEE Geosci. Remote Sens. Lett., vol. 10, no. 4, pp. 682-686, Jul. 2013.
    • (2013) IEEE Geosci. Remote Sens. Lett. , vol.10 , Issue.4 , pp. 682-686
    • Yin, J.1    Gao, C.2    Jia, X.3
  • 17
    • 0034296402 scopus 로고    scopus 로고
    • Generalized discriminant analysis using a kernel approach
    • Oct.
    • G. Baudat and F. Anouar, "Generalized discriminant analysis using a kernel approach," Neural Comput., vol. 12, no. 10, pp. 2385-2404, Oct. 2000.
    • (2000) Neural Comput. , vol.12 , Issue.10 , pp. 2385-2404
    • Baudat, G.1    Anouar, F.2
  • 19
    • 2642530204 scopus 로고    scopus 로고
    • Nonparametric weighted feature extraction for classification
    • May
    • B. C. Kuo and D. A. Landgrebe, "Nonparametric weighted feature extraction for classification," IEEE Trans. Geosci. Remote Sens, vol. 42, no. 5, pp. 1096-1105, May 2004.
    • (2004) IEEE Trans. Geosci. Remote Sens , vol.42 , Issue.5 , pp. 1096-1105
    • Kuo, B.C.1    Landgrebe, D.A.2
  • 20
    • 82055188364 scopus 로고    scopus 로고
    • A new fast algorithm for multiclass hyperspectral image classification with SVM
    • Dec.
    • S. A. Hosseini and H. Ghassemian, "A new fast algorithm for multiclass hyperspectral image classification with SVM," Int. J. Remote Sens., vol. 32, no. 23, pp. 8657-8683, Dec. 2011.
    • (2011) Int. J. Remote Sens. , vol.32 , Issue.23 , pp. 8657-8683
    • Hosseini, S.A.1    Ghassemian, H.2
  • 22
    • 3042661357 scopus 로고    scopus 로고
    • Thematic map comparison: Evaluating the statistical significance of differences in classification accuracy
    • G. M. Foody, "Thematic map comparison: Evaluating the statistical significance of differences in classification accuracy," Photogramm. Eng. Remote Sens., vol. 70, no. 5, pp. 627-633, 2004. (Pubitemid 39081774)
    • (2004) Photogrammetric Engineering and Remote Sensing , vol.70 , Issue.5 , pp. 627-633
    • Foody, G.M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.