Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1781465 | Planetary and Space Science | 2012 | 8 Pages |
Abstract
This paper 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.
Keywords
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Geophysics
Authors
Konstantinos E. Themelis, Frédéric Schmidt, Olga Sykioti, Athanasios A. Rontogiannis, Konstantinos D. Koutroumbas, Ioannis A. Daglis,