By Topic

The Physical Meaning of Independent Components and Artifact Removal of Hyperspectral Data from Mars using ICA

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
H. Hauksdottir ; University of Iceland, Reykjavík, Iceland; Images and Signals Laboratory, Institut National Polytechnique de Grenoble, Grenoble, France ; C. Jutten ; F. Schmidt ; J. Chanussot
more authors

The truth about what chemicals are to be found on the surface of Mars lies hidden in Gigabytes of hyperspectral data. How to reveal this mystery is the subject of this paper. Independent component analysis (ICA) is used for identification and classification of endmembers and for artifact removal. The classification results are compared with the result of a wavelet classifier and reference spectra are used for identification of known substances. CO2 ice and water ice and an intimate mixture of CO2 ice and dust are effectively found as independent components, but because of high negative correlation of dust and CO2 ice, dust is not found as a separate component. ICA can be used to valuate the atmospheric effect removal, which is currently being used and can help in this preprocessing. ICA can also be used for other artifacts, such as to find and clean corrupted channels and to detect the effect of the overlay of sensors. It is proposed to view the mixing matrix as a collection of independent components (ICs) spectra, and use this for automatic detection of known endmembers

Published in:

Proceedings of the 7th Nordic Signal Processing Symposium - NORSIG 2006

Date of Conference:

7-9 June 2006