On the unmixing of MEx/OMEGA hyperspectral data

K.E. Themelis (1, 2) , F. Schmidt (3) , O. Sykioti (2) , A.A. Rontogiannis (2) , K.D. Koutroumbas (2) , I.A. Daglis (2)

1 Dpt of Informatics & Telecommunications
2 Institute for Space Applications and Remote Sensing
3 IDES - Interactions et dynamique des environnements de surface

This paper presents a comparative study of three different types of estimators used for supervised linear unmixing of two MEx/OMEGAhyperspectral 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.

Domaines: Sciences de la Terre

K.E. Themelis, F. Schmidt, O. Sykioti, A.A. Rontogiannis, K.D. Koutroumbas, et al.. On the unmixing of MEx/OMEGA hyperspectral data. Planetary and Space Science, 2012, 68 (1), pp.34-41. ⟨10.1016/j.pss.2011.11.015⟩. ⟨hal-00675181⟩