Texture-Invariant Estimation of Equivalent Number of Looks Based on Trace Moments in Polarimetric Radar Imagery

This letter introduces a novel estimator of equivalent number of looks (ENL) that can be applied to any distribution of texture model, i.e., an estimator that is texture invariant. The novel estimator is the Development of Trace Moments (DTM), which cancels the textural variation using trace moments. Five forms of the DTM estimator using submatrices are presented and compared with each other. The results show that the full-dimensional matrix form seems to be the best in performance and computational complexity. The experiments were performed using simulated and real data. The comparisons among all the existing methods of ENL estimation in the product model of the clutter, such as K-distribution and G0 distribution, show the performance of the DTM estimator to be the best if there is a sufficient number of samples. The global and local ENL estimations of the real data of San Francisco are analyzed, and the results agree with the simulated case. This shows that the DTM always gives a good result, particularly in the global estimation of ENL. Therefore, it can be concluded that the DTM estimator is robust to any distribution model, with low computational complexity and high accuracy, particularly in wide areas with similar scattering mechanism.