An iterative least squares approach to decorrelate minerals and ices contributions in hyperspectral images : application to cuprite (Earth) and Mars

Research areas:
Year:
2009
Authors:
Book title:
2009 FIRST WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING
Pages:
438-441
Organization:
IEEE Geosci & Remote Sensing Soc
ISBN:
978-1-4244-4686-5
Note:
1st Workshop on Hyperspectral Image and Signal Processing - Evolution in Remote Sensing, Grenoble, FRANCE, AUG 26-29, 2009
Abstract:
We present an Iterative Linear Spectral Unmixing Model (ILSUM) which is
aimed at finding the main surface components that contribute to the
signal in visible and infrared hyperspectral images. We processed the
global dataset of the OMEGA imaging spectrometer onboard Mars Express up
to orbit 5300, covering two martian years. We also present a preliminary
test on AVIRIS data on the Cuprite (Nevada) site. We use ILSUM to
identify the contribution of each endmember of an input library
containing laboratory spectra of ices and mineral powders that are
representative of the main mineral families. Synthetic spectra (pure
slope endmembers) are included to account at first order for aerosol and
grain size variations. Applied to the global OMEGA data set, this
algorithm provides a distribution map for the main minerals present on
the martian surface, which appears to be mainly dominated by pyroxenes,
olivine, ferric oxides, with localized exposures of sulfates and
phyllosilicates.