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IGARSS
2009

Endmember Extraction from Hyperspectral Imagery using a Parallel Ensemble Approach with Consensus Analysis

9 years 5 months ago
Endmember Extraction from Hyperspectral Imagery using a Parallel Ensemble Approach with Consensus Analysis
We have explored in this paper a framework to test in a quantitative manner the stability of different endmember extraction and spectral unmixing algorithms based on the concept of Consensus Clustering. The idea is to investigate if the sensibility of those algorithms to the number of endmembers can be used to estimate this parameter itself. Preliminary results on synthetic data reveal that the proposed scheme, which can be implemented efficiently in parallel, can compete with state-of-the-art schemes.
Fermin Ayuso, Javier Setoain, Manuel Prieto, Chris
Added 20 Feb 2011
Updated 20 Feb 2011
Type Journal
Year 2009
Where IGARSS
Authors Fermin Ayuso, Javier Setoain, Manuel Prieto, Christian Tenllado, Francisco Tirado, Javier Plaza, Antonio Plaza
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