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Proceedings Paper

Spectral unmixing using nonnegative basis learning: comparison of geometrical and statistical endmember extraction algorithms
Author(s): Mario Parente
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Paper Abstract

Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) data can be used to identify the presence of minerals on the surface or Mars. The data are a peculiar set from which to extract endmembers. Using an image from a previously investigate area of the surface, we compare a geometrical and a statistical algorithm for extracting endmembers for mineral identification. Both algorithms correctly identified the spectra of the two minerals known to be present in the Nili Fossae region of Mars. Both algorithms suffer from linearity assumption. Even though the statistical algorithm is less robust with respect to outliers, it has potential to extract endmembers in complex data clouds because of its local nature.

Paper Details

Date Published: 15 April 2008
PDF: 13 pages
Proc. SPIE 6960, Space Exploration Technologies, 69600P (15 April 2008); doi: 10.1117/12.777895
Show Author Affiliations
Mario Parente, Stanford Univ. (United States)

Published in SPIE Proceedings Vol. 6960:
Space Exploration Technologies
Wolfgang Fink, Editor(s)

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