Abstract:

The unmixing of hyper-spectral data is the crucial base of qualitative and quantitative analysis of rock minerals. The simulated or measured hyper-spectral data can be analyzed with the FastICA algorithm to calculate the number of pure-pixels as well as the spectrum of each pure-pixel. Based on the results, the mineral abundance inversion can be carried out. The experiments show that the FastICA algorithm can effectively un-mix the mineral hyper-spectrum and estimate the spectrum of each pure-pixel, even when there is no prior knowledge of the spectrum or the mixing matrix of pure-pixels. This facilitates the mineral identification and the mineral abundance inversion. However, when the spectrums of the pure-pixels are highly similar or the non-gaussianity is bad, the precision of the mineral identification would be reduced, which in turn reduces the precision of mineral abundance inversion and vice versa.

Key words: FastICA, hyper-spectrum, mixed pixel, mineral abundance inversion, minerals