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Proceedings Paper

Unsupervised unmixing analysis based on multiscale representation
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Paper Abstract

Automated unmixing consists of finding the number of endmembers, their spectral signatures and their abundances from a hyperspectral image. Most unmixing techniques are pixel-to-pixel procedures that do not take advantage of spatial information provided by hyperspectral sensor. This paper explores a new approach for unmixing analysis of hyperspectral imagery based on a multiscale representation for the joint estimation of the number of endmember and their spectral signatures. Experimental results using an AVIRIS image is presented.

Paper Details

Date Published: 24 May 2012
PDF: 11 pages
Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83901O (24 May 2012); doi: 10.1117/12.920698
Show Author Affiliations
Maria C. Torres-Madronero, Univ. de Puerto Rico Mayagüez (United States)
Miguel Velez-Reyes, Univ. de Puerto Rico Mayagüez (United States)


Published in SPIE Proceedings Vol. 8390:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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