Endmember initialization method for hyperspectral data unmixing

Rui Wang, Hengchao Li, Wenzhi Liao, Xin Huang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Spectral unmixing aims at finding the spectrally pure constituent materials (also called endmembers) and their respective fractional abundances in each pixel of the hyperspectral image scene. One important issue in hyperspectral data unmixing is the initialization of endmembers. Most unmixing methods initialize their endmembers by randomly selecting a specified number of pixels from the data or by vertex component analysis, which limits their performance in practice. We propose an endmember initialization method for hyperspectral data unmixing. Our initial endmembers include some of the true endmembers, which improves the accuracy of hyperpspectral unmixing effectively. The experimental results on both synthetic and real hyperspectral data illustrate the superiority of the proposed method compared with other state-of-the-art approaches.

Original languageEnglish
Article number042009
JournalJournal of Applied Remote Sensing
Volume10
Issue number4
DOIs
StatePublished - Oct 1 2016
Externally publishedYes

Keywords

  • Hyperspectral data
  • initialization
  • nonnegative matrix factorization
  • nuclear norm
  • unmixing

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