On the unmixing of MEx/OMEGA hyperspectral data

Konstantinos E. Themelis; Frédéric Schmidt; Olga Sykioti; Athanasios A. Rontogiannis; Konstantinos D. Koutroumbas; Ioannis A. Daglis

doi:10.1016/j.pss.2011.11.015

arXiv · 1112.1527

On the unmixing of MEx/OMEGA hyperspectral data

Konstantinos E. Themelis·Frédéric Schmidt·Olga Sykioti·Athanasios A. Rontogiannis·Konstantinos D. Koutroumbas·Ioannis A. Daglis

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Abstract

This article presents a comparative study of three different types of estimators used for supervised linear unmixing of two MEx/OMEGA hyperspectral cubes. The algorithms take into account the constraints of the abundance fractions, in order to get physically interpretable results. Abundance maps show that the Bayesian maximum a posteriori probability (MAP) estimator proposed in Themelis and Rontogiannis (2008) outperforms the other two schemes, offering a compromise between complexity and estimation performance. Thus, the MAP estimator is a candidate algorithm to perform ice and minerals detection on large hyperspectral datasets.

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BibTeX RIS

Konstantinos E. Themelis, Frédéric Schmidt, Olga Sykioti, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas, Ioannis A. Daglis. 2011-12-07. On the unmixing of MEx/OMEGA hyperspectral data. https://doi.org/10.1016/j.pss.2011.11.015

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