PolInSAR Complex Coherence Estimation Based on Covariance Matrix Similarity Test

Most polarimetric synthetic aperture radar interferometry (PolInSAR) data processing procedures and their applications are based on the polarimetric complex coherence descriptor. The reliable estimation of the complex coherence requires selecting sufficient homogeneous pixels for generating an unbiased estimator. In this paper, two indicators using only polarimetric and both polarimetric and interferometric information are derived as the similarity measures for complex Wishart distributed PolInSAR covariance matrix, respectively. Using these indicators, a double similarity test scheme, which shows high sensitivity to both polarimetric and interferometric properties, is proposed for similar pixel selection. The full information utilization could characterize the homogeneous pixels more accurately. Furthermore, since the similarity test has the potential to reject the pixels with different populations, it is suitable to be applied in a large searching area (e.g., 15 × 15 window) to accept sufficient homogeneous pixels. Thereby, combining with unbiased estimator, reliable estimation is achieved. The efficiency and advantage of the proposed estimation scheme are demonstrated with the aid of simulated and real PolInSAR data sets.