  We present the first application of a new foreground removal pipeline to the
current leading HI intensity mapping dataset, obtained by the Green Bank
Telescope (GBT). We study the 15hr and 1hr field data of the GBT observations
previously presented in Masui et al (2013) and Switzer et al (2013), covering
about 41 square degrees at 0.6<z<1.0, for which cross-correlations may be
measured with the galaxy distribution of the WiggleZ Dark Energy Survey. In the
presented pipeline, we subtract the Galactic foreground continuum and the point
source contamination using an independent component analysis technique
(fastica), and develop a Fourier-based optimal estimator to compute the
temperature power spectrum of the intensity maps and cross-correlation with the
galaxy survey data. We show that fastica is a reliable tool to subtract diffuse
and point-source emission through the non-Gaussian nature of their probability
distributions. The temperature power spectra of the intensity maps is dominated
by instrumental noise on small scales which fastica, as a conservative
subtraction technique of non-Gaussian signals, can not mitigate. However, we
determine similar GBT-WiggleZ cross-correlation measurements to those obtained
by the Singular Value Decomposition (SVD) method, and confirm that foreground
subtraction with fastica is robust against 21cm signal loss, as seen by the
converged amplitude of these cross-correlation measurements. We conclude that
SVD and fastica are complementary methods to investigate the foregrounds and
noise systematics present in intensity mapping datasets.
