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

• Published in: 2006 7th Nordic Signal Processing Symposium, 2006 : Reykjayik [i.e. Reykjavik], Iceland, 7-9 June 2006 pp. 226 - 229
• Main Authors: Hauksdottir, H., Jutten, C., Schmidt, E., Chanussot, J., Benediktsson, J.A., Doute, S.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2006
• Subjects: Additives; Chemical sensors; Hyperspectral imaging; Hyperspectral sensors; Ice; Independent component analysis; Infrared sensors; Instruments; Laboratories; Mars
• ISBN: 9781424404124; 1424404126
• DOI: 10.1109/NORSIG.2006.275229

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. CO 2 ice and water ice and an intimate mixture of CO 2 ice and dust are effectively found as independent components, but because of high negative correlation of dust and CO 2 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