• DocumentCode
    2669765
  • Title

    A new scheme for decomposition of mixed pixels based on nonnegative matrix factorization

  • Author

    Tao, Xuetao ; Wang, Bin ; Zhang, Liming ; Zhang, Jian Qiu

  • Author_Institution
    Fudan Univ., Shanghai
  • fYear
    2007
  • fDate
    23-28 July 2007
  • Firstpage
    1759
  • Lastpage
    1762
  • Abstract
    The simplex-based methods are a kind of the most important and widely used methods for the decomposition of mixed pixels in multispectral and hyperspectral remote sensing images, which need a strong basic hypothesis that there is at least one pure pixel for every endmember existing in the images. N- FINDR is of typical sense in this kind of methods, and it also needs this basic hypothesis. Unfortunately, the precision for the decomposition of mixed pixels will be seriously influenced if this hypothesis cannot be met in practice. This paper presents a new scheme based on Nonnegative Matrix Factorization (NMF) to solve this problem. In addition, some appropriate constrains are introduced into NMF for the decomposition of mixed pixels. Experimental results obtained from both artificial simulated and real-world remote sensing data demonstrate that the proposed scheme for decomposition of mixed pixels has excellent analytical performance.
  • Keywords
    image processing; matrix decomposition; remote sensing; N- FINDR method; hyperspectral remote sensing images; mixed pixels decomposition; multispectral remote sensing images; nonnegative matrix factorization; Analytical models; Hyperspectral imaging; Hyperspectral sensors; Indexes; Matrix decomposition; Performance analysis; Pixel; Reflectivity; Remote sensing; Spectral analysis; decomposition of mixed pixels; hyperspectral/multispectral remote sensing images; nonnegative matrix factorization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
  • Conference_Location
    Barcelona
  • Print_ISBN
    978-1-4244-1211-2
  • Electronic_ISBN
    978-1-4244-1212-9
  • Type

    conf

  • DOI
    10.1109/IGARSS.2007.4423160
  • Filename
    4423160