• DocumentCode
    1515626
  • Title

    On the Convergence of N-FINDR and Related Algorithms: To Iterate or Not to Iterate?

  • Author

    Dowler, Shaun ; Andrews, Mark

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Auckland, Auckland, New Zealand
  • Volume
    8
  • Issue
    1
  • fYear
    2011
  • Firstpage
    4
  • Lastpage
    8
  • Abstract
    A popular algorithm for unmixing hyperspectral data, namely, Winter´s N-FINDR algorithm, is frequently used to benchmark other algorithms or as the basis for new algorithms. The interpretations of this algorithm within the literature are not consistent, and some of these differences have significant impact on the convergence of the algorithm. Despite this, the differences in implementation have not been explicitly acknowledged within the literature, which means that many studies are now ambiguous or incomparable. An examination of various implementations of the N-FINDR algorithm highlights that not all interpretations possess the properties asserted by Winter and that interpretations that consider each pixel multiple times generate much larger simplexes. Regardless of which implementation researchers choose to use, if they are explicit in their choice, this would allow for unambiguous comparisons.
  • Keywords
    algorithm theory; N-FINDR algorithm; algorithm convergence; unmixing hyperspectral data; Algorithm design and analysis; Convergence; Gaussian noise; Hyperspectral imaging; Layout; Solid modeling; Vectors; Hyperspectral; N-FINDR; unmixing;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2010.2049639
  • Filename
    5484534