메뉴 건너뛰기




Volumn 34, Issue 19, 2013, Pages 6577-6586

A new non-negative matrix factorization method based on barycentric coordinates for endmember extraction in hyperspectral remote sensing

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL MECHANICS; EXTRACTION; FACTORIZATION; PIXELS; REMOTE SENSING; SPECTROSCOPY;

EID: 84880172480     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2013.804223     Document Type: Article
Times cited : (9)

References (22)
  • 2
    • 0002081183 scopus 로고
    • Automated Spectral Unmixing of AVIRIS Data Using Convex Geometry Concepts
    • Pasadena, CA, Pasadena, CA,: JPL Publication
    • Boardman, J. W. 1993. " Automated Spectral Unmixing of AVIRIS Data Using Convex Geometry Concepts ". In 4th JPL Airborne Geoscience Workshop, 93 - 26. Pasadena, CA: JPL Publication.
    • (1993) 4th JPL Airborne Geoscience Workshop , pp. 26-93
    • Boardman, J.W.1
  • 3
    • 1842481516 scopus 로고    scopus 로고
    • Estimation of Number of Spectrally Distinct Signal Sources in Hyperspectral Imagery
    • Chang, C.-I. and Du, Q. 2004. Estimation of Number of Spectrally Distinct Signal Sources in Hyperspectral Imagery. IEEE Transactions on Geoscience and Remote Sensing, 42: 608 - 619.
    • (2004) IEEE Transactions on Geoscience and Remote Sensing , vol.42 , pp. 608-619
    • Chang, C.-I.1    Du, Q.2
  • 7
    • 77951125385 scopus 로고    scopus 로고
    • A New Volume Formula for a Simplex and its Application to Endmember Extraction for Hyperspectral Image Analysis
    • Geng, X., Zhao, Y., Wang, F. and Gong, P. 2010. A New Volume Formula for a Simplex and its Application to Endmember Extraction for Hyperspectral Image Analysis. International Journal of Remote Sensing, 31: 1027 - 1035.
    • (2010) International Journal of Remote Sensing , vol.31 , pp. 1027-1035
    • Geng, X.1    Zhao, Y.2    Wang, F.3    Gong, P.4
  • 10
    • 84861345596 scopus 로고    scopus 로고
    • Geometric Unmixing of Large Hyperspectral Images: A Barycentric Coordinate Approach
    • Honeine, P. and Richard, C. 2012. Geometric Unmixing of Large Hyperspectral Images: A Barycentric Coordinate Approach. IEEE Transactions on Geoscience and Remote Sensing, 50: 2185 - 2195.
    • (2012) IEEE Transactions on Geoscience and Remote Sensing , vol.50 , pp. 2185-2195
    • Honeine, P.1    Richard, C.2
  • 13
    • 0033592606 scopus 로고    scopus 로고
    • Learning the Parts of Objects by Nonnegative Matrix Factorization
    • Lee, D. and Seung, S. 1999. Learning the Parts of Objects by Nonnegative Matrix Factorization. Nature, 401: 788 - 791.
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.1    Seung, S.2
  • 14
    • 33847733865 scopus 로고    scopus 로고
    • Endmember Extraction from Highly Mixed Data Using Minimum Volume Constrained Nonnegative Matrix Factorization
    • Lidan, M. and Hairong, Q. 2007. Endmember Extraction from Highly Mixed Data Using Minimum Volume Constrained Nonnegative Matrix Factorization. IEEE Transactions on Geoscience and Remote Sensing, 45: 765 - 777.
    • (2007) IEEE Transactions on Geoscience and Remote Sensing , vol.45 , pp. 765-777
    • Lidan, M.1    Hairong, Q.2
  • 16
    • 84855445002 scopus 로고    scopus 로고
    • A New Maximum Simplex Volume Method Based on Householder Transformation for Endmember Extraction
    • Liu, J. and Zhang, J. 2012. A New Maximum Simplex Volume Method Based on Householder Transformation for Endmember Extraction. IEEE Transactions on Geoscience and Remote Sensing, 50: 104 - 118.
    • (2012) IEEE Transactions on Geoscience and Remote Sensing , vol.50 , pp. 104-118
    • Liu, J.1    Zhang, J.2
  • 19
    • 33646682646 scopus 로고    scopus 로고
    • Nonnegative Matrix Factorization for Spectral Data Analysis
    • Pauca, V. P. 2006. Nonnegative Matrix Factorization for Spectral Data Analysis. Linear Algebra and Its Applications, 416: 29 - 47.
    • (2006) Linear Algebra and Its Applications , vol.416 , pp. 29-47
    • Pauca, V.P.1
  • 22
    • 34547229626 scopus 로고    scopus 로고
    • Sparsity Promoting Iterated Constrained Endmember Detection in Hyperspectral Imagery
    • Zare, A. and Gader, P. 2007. Sparsity Promoting Iterated Constrained Endmember Detection in Hyperspectral Imagery. Geoscience and Remote Sensing Letters, IEEE, 4: 446 - 450.
    • (2007) Geoscience and Remote Sensing Letters, IEEE , vol.4 , pp. 446-450
    • Zare, A.1    Gader, P.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.