Evaluation of the New Information in the ${H}/\alpha$ Feature Space Provided by ICA in PolSAR Data Analysis

Abstract

The Cloude and Pottier $H/\alpha $ feature space is one of the most employed methods for unsupervised polarimetric synthetic aperture radar (PolSAR) data classification based on incoherent target decomposition (ICTD). The method can be split in two stages: the retrieval of the canonical scattering mechanisms present in an image cell and their parameterization. The association of the coherence matrix eigenvectors to the most dominant scattering mechanisms in the analyzed pixel introduces unfeasible regions in the $H/\alpha $ plane. This constraint can compromise the performance of detection, classification, and geophysical parameter inversion algorithms that are based on the investigation of this feature space. The independent component analysis (ICA), recently proposed as an alternative to eigenvector decomposition, provides promising new information to better interpret non-Gaussian heterogeneous clutter (inherent to high-resolution SAR systems) in the frame of polarimetric ICTDs. 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/\alpha $ plane, increasing the range of possible natural phenomena depicted in the aforementioned feature space. This paper addresses the potential of the new information provided by the ICA as an ICTD method with respect to Cloude and Pottier $H/\alpha $ feature space. A PolSAR data set acquired in October 2006 by the E-SAR system over the upper part of the Tacul glacier from the Chamonix Mont Blanc test site, France, and a RAMSES X-band image acquired over Bretigny, France, are taken into consideration to investigate the characteristics of pixels that may fall outside the feasible regions in the $H/\alpha $ plane that arise when the eigenvector approach is employed.