Non-linear correction of polarization orientation for the application of ICA to PolSAR imagery

In this paper, we discuss invalidity of the linear mixture model of independent component analysis (ICA) and evaluate an estimation method for the polarization orientation (PO) angle in order to correct the mismatched data model regarding unmixing signals of polarimetric SAR imagery. Firstly, the linear mixture model of ICA and the nonlinear mixture model of the PO effect are described so that we refer to distorted assumption. Then, a correction method for the PO angle is introduced and tested with single- and multi-temporal L-band images in two areas. We employ two indices of class separation and statistical independence for evaluation since they are supported concerning fundamental theory and the scale problem of ICA. They show its performance of feature extraction and recovery from the invalid mixture model. With these results, we show the effectiveness of nonlinear correction for the application of ICA to polarimetric SAR imagery.