DocumentCode :
3237120
Title :
How to Apply ICA on Actual Data ? Example of Mars Hyperspectral Image Analysis
Author :
Jutten, Christian ; Moussaoui, Said ; Schmidt, Frédéric
Author_Institution :
GIPSA-lab., Grenoble
fYear :
2007
fDate :
1-4 July 2007
Firstpage :
3
Lastpage :
12
Abstract :
As any estimation method, results provided by ICA are dependent of a model - usually a linear mixture and separation model - and of a criterion - usually independence. In many actual problems, the model is a coarse approximation of the system physics and independence can be more or less satisfied, and consequently results are not reliable. Moreover, with many actual data, there is a lack of reliable knowledge on the sources to be extracted, and the interpretation of the independent components (IC) must be done very carefully, using partial prior information and with interactive discussions with experts. In this talk, we explain how such a scientific method can take place on the example of analysis of Mars hyperspectral images.
Keywords :
Mars; astronomical image processing; independent component analysis; Mars hyperspectral images; hyperspectral image analysis; independent component analysis; linear mixture; separation model; Biomedical signal processing; Hyperspectral imaging; Hyperspectral sensors; Image analysis; Independent component analysis; Mars; Parametric statistics; Physics; Signal processing algorithms; Source separation; Bayesian source separation; Mars Express; hyperspectral images; independent component analysis; positivity; source separation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing, 2007 15th International Conference on
Conference_Location :
Cardiff
Print_ISBN :
1-4244-0882-2
Electronic_ISBN :
1-4244-0882-2
Type :
conf
DOI :
10.1109/ICDSP.2007.4288502
Filename :
4288502
Link To Document :
بازگشت