Information extraction by blind source separation from polarimetric SAR data
Cloude and Pottier H/α feature space [1] is one of the most employed methods for unsupervised PolSAR data classification based on Incoherent Target Decomposition. The association of the coherence matrix eigenvectors to the most dominant scatters in the analysed pixel introduces unfeasible regions in the H/α plane. The Independent Component Analysis provides promising new information to better interpret non-Gaussian heterogeneous clutter in the frame of polarimetric incoherent target decompositions. Not constrained to any orthogonality between the estimated scattering mechanisms that compose the clutter under analysis, ICA does not introduce any unfeasible region in the H/α plane, increasing the range of possible natural phenomenons depicted in the aforementioned feature space.