Intensity-driven-adaptive-neighborhood technique for POLSAR parameters estimation
In this paper, a new method to estimate polarimetric coherency matrices and derive associated parameters is presented. For each pixel of the data set, an adaptive neighborhood is computed by a region growing technique driven exclusively by the intensity images. The three intensity images of the POLSAR acquisition are fused in the region growing process to ensure the stationarity hypothesis of the derived statistical population. Then, all pixels within the obtained adaptive neighborhood are, either complex averaged or estimated by the locally linear minimum mean squared error (LLMMSE), to yield a feature preserving reliable estimate of the polarimetric coherency matrix. The target entropy/alpha/anisotropy decomposition is applied on the derived polarimetric coherency matrix. Using this decomposition, unsupervised classifcation for land applications by an iterative algorithm based on a complex Wishart density function is employed. The method has been tested on airborne polarimetric synthetic aperture radar images (Northumberland Strait costal area - Canadian Space Agency).