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End-member extraction for hyperspectral image analysis.

Authors
  • Du, Qian
  • Raksuntorn, Nareenart
  • Younan, Nicolas H
  • King, Roger L
Type
Published Article
Journal
Applied Optics
Publisher
The Optical Society
Publication Date
Oct 01, 2008
Volume
47
Issue
28
Identifiers
PMID: 18830287
Source
Medline
License
Unknown

Abstract

We investigate the relationship among several popular end-member extraction algorithms, including N-FINDR, the simplex growing algorithm (SGA), vertex component analysis (VCA), automatic target generation process (ATGP), and fully constrained least squares linear unmixing (FCLSLU). We analyze the fundamental equivalence in the searching criteria of the simplex volume maximization and pixel spectral signature similarity employed by these algorithms. We point out that their performance discrepancy comes mainly from the use of a dimensionality reduction process, a parallel or sequential implementation mode, or the imposition of certain constraints. Instructive recommendations in algorithm selection for practical applications are provided.

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