Abstract:The K-distribution is usually used to model the Polarimetric Synthetic Aperture Radar (PolSAR) imagery. The parameter estimation method for K-distribution is very important,which affects the fitting degree of the model. However, the classical method of matrix log-cumulants relies upon a nontrivial inversion of a nonlinear equation, which introduces a computationally expensive stage into the estimation procedure. Moreover, the bias is large when the sharp parameter α is smaller than 1. Therefore, a new method for estimating the sharp parameter of K-distribution based on |z|rlg|z| is proposed. This method is more adaptable to parameter estimation under different sharp parameters, and the performance is better than matrix log-cumulantes when α is small. In addition, the proposed estimator has an analytical expression at r=1/d, which allows rapid caculation. Finally, the estimation accuracy of this new estimator is compared with previous ones through simulation data and real data. The results show that the new estimator is effective and robust, which is of practical value in solving the accurate parameter estimation of K-distribution.
崔浩贵, 刘涛, 蒋宇中, 高俊. 基于混合矩的极化SAR图像K分布模型参数估计新方法[J]. 电子与信息学报, 2015, 37(2): 328-333.
Cui Hao-Gui, Liu Tao, Jiang Yu-Zhong, Gao Jun. Parameter Estimation for the K-distribution in PolSAR Imagery Based on Hybrid Moments. , 2015, 37(2): 328-333.