Laser & Optoelectronics Progress, Volume. 56, Issue 9, 091001(2019)

Improved Algorithm for Nonnegative Matrix Factorization and Endmember Extraction Based on Data Simplification

Jun Xu1、*, Xuhong Wang2, and Cailing Wang3
Author Affiliations
  • 1 School of Electronic Engineering, Xi'an Aeronautical University, Xi'an, Shaanxi 710077, China
  • 2 College of Urban and Environmental Sciences, Northwest University, Xi'an, Shaanxi 710127, China
  • 3 School of Computer Science, Xi'an Shiyou University, Xi'an, Shaanxi 710065, China
  • show less
    References(14)

    [8] Yang H D. Research on spectral unmixing algorithms for hyperspectral remote sensing image[D]. Dalian: Dalian Maritime University, 70-79(2015).

    [12] Bioucas-Dias J M, Nascimento J M P. Hyperspectral subspace identification[J]. IEEE Transactions on Geoscience and Remote Sensing, 46, 2435-2445(2008).

    [13] Peng Q. Hyperspectral unmixing based on constrained nonnegative matrix factorization[D]. Beijing: University of Chinese Academy of Sciences(2017).

    Tools

    Get Citation

    Copy Citation Text

    Jun Xu, Xuhong Wang, Cailing Wang. Improved Algorithm for Nonnegative Matrix Factorization and Endmember Extraction Based on Data Simplification[J]. Laser & Optoelectronics Progress, 2019, 56(9): 091001

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Image Processing

    Received: Oct. 10, 2018

    Accepted: Nov. 23, 2018

    Published Online: Jul. 5, 2019

    The Author Email: Xu Jun (3225393639@qq.com)

    DOI:10.3788/LOP56.091001

    Topics