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Proceedings Paper

Stepwise simplex projection method for selection of endmembers in hyperspectral images
Author(s): Peter Bajorski
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Paper Abstract

In previous research, we introduced a family of simplex projection methods for selection of endmembers in hyperspectral images. In this paper, we define a new member of that family, which we call the Stepwise Simplex Projection (SSP) method. This new method adds and eliminates endmembers based on their distances to simplexes defined by previously chosen endmembers. We compare the SSP method to a previously defined simplex projection method (called the Farthest Pixel Selection method) and to some other methods such as the Pixel Purity Index and Maximum Distance methods. To this end, we introduce several summary measures to describe how well a set of endmembers characterizes the image spectra. We also investigate how well the resulting sets of endmembers perform in subpixel target detection. The numerical results are based on AVIRIS hyperspectral imagery. The SSP method proves to be the most consistently well performing among the investigated methods.

Paper Details

Date Published: 1 June 2005
PDF: 12 pages
Proc. SPIE 5806, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI, (1 June 2005); doi: 10.1117/12.603433
Show Author Affiliations
Peter Bajorski, Rochester Institute of Technology (United States)


Published in SPIE Proceedings Vol. 5806:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XI
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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