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Volumn , Issue , 2012, Pages 3054-3057

Hyperspectral band selection using a collaborative sparse model

Author keywords

band selection; hyperspectral imaging; support vector machine based classification

Indexed keywords

BAND SELECTION; CLASSIFICATION ACCURACY; FAST METHODS; HYPERSPECTRAL; HYPERSPECTRAL IMAGING; LINEAR REGRESSION COEFFICIENTS; PRE-SELECTED; SPARSENESS CONSTRAINTS; SUPPORT VECTOR;

EID: 84873103655     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IGARSS.2012.6350781     Document Type: Conference Paper
Times cited : (45)

References (8)
  • 1
    • 33846570487 scopus 로고    scopus 로고
    • A novel geometry-based feature-selection technique for hyperspectral imagery
    • Jan.
    • L. Wang, X. Jia, and Y. Zhang, "A novel geometry-based feature-selection technique for hyperspectral imagery," IEEE Geosciencce Remote Sensing Letters, vol. 4, no. 1, pp. 171-175, Jan. 2007.
    • (2007) IEEE Geosciencce Remote Sensing Letters , vol.4 , Issue.1 , pp. 171-175
    • Wang, L.1    Jia, X.2    Zhang, Y.3
  • 2
    • 55649124564 scopus 로고    scopus 로고
    • Similarity-based unsupervised band selection for hyperspectral image analysis
    • Oct.
    • Q. Du and H. Yang, "Similarity-based unsupervised band selection for hyperspectral image analysis," IEEE Geoscience and Remote Sensing Letters, vol. 5, no. 4, pp. 564-568, Oct. 2008.
    • (2008) IEEE Geoscience and Remote Sensing Letters , vol.5 , Issue.4 , pp. 564-568
    • Du, Q.1    Yang, H.2
  • 3
    • 0035273728 scopus 로고    scopus 로고
    • Fully constrained least squares linear Spectral mixture analysis method for material quantification in hyperspectral imagery
    • Mar.
    • D. C. Heinz, C. I. Chang, "Fully constrained least squares linear Spectral mixture analysis method for material quantification in hyperspectral imagery", IEEE Trans. Geoscience Remote Sensing, vol. 39, no. 3, pp. 529-545, Mar. 2001.
    • (2001) IEEE Trans. Geoscience Remote Sensing , vol.39 , Issue.3 , pp. 529-545
    • Heinz, D.C.1    Chang, C.I.2
  • 4
    • 0033310314 scopus 로고    scopus 로고
    • N-FINDR: An algorithm for fast autonomous spectral endmember determination in hyperspectral data
    • M. E. Winter, "N-FINDR: An algorithm for fast autonomous spectral endmember determination in hyperspectral data," Proc. SPIE, vol. 3753, pp. 266-275, 1999.
    • (1999) Proc. SPIE , vol.3753 , pp. 266-275
    • Winter, M.E.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.