Polarimetric scattering indexes and information entropy of the SAR imagery for surface monitoring

The Mueller matrix solution and eigenanalysis of the coherency matrix for completely polarimetric scattering have been applied to the analysis of synthetic aperture radar (SAR) imagery. Copolarized and cross-polarized backscattering for any polarized incidence can be obtained. The polarization index is usually defined as a parameter to classify the difference between polarized scattering signatures from the terrain surfaces. The eigenvalues of the coherency matrix and information entropy are derived to directly relate with measurements of the copolarized and cross-polarized indexes. Thus, it combines the Mueller matrix simulation, the information entropy of the coherence matrix, and two polarization indexes together and yields a quantitative evaluation for surface classification in the SAR imagery. This theory is applied to analysis of the AirSAR images and field measurements.