A fast and adaptive method for complex-valued SAR image denoising based on l_k norm regularization  

作　　者：WANG WeiWei WANG ZhengMing YUAN ZhenYu LI MingShan 

机构地区：[1]College of Information System and Management, National University of Defence Technology, Changsha 410073, China [2]College of Science, National University of Defence Technology, Changsha 410073, China

出　　处：《Science in China(Series F)》2009年第1期138-148,共11页中国科学（F辑英文版）

基　　金：Supported by the National Natural Science Foundation of China (Grant No. 60572136);the Fundamental Research Fund of NUDT (Grant No.JC0702005)

摘　　要：This paper developed a fast and adaptive method for SAR complex image denoising based on lk norm regularization, as viewed from parameters estimation. We firstly establish the relationship between denoising model and ill-posed inverse problem via convex half-quadratic regularization, and compare the difference between the estimator variance obtained from the iterative formula and biased CramerRao bound, which proves the theoretic flaw of the existent methods of parameter selection. Then, the analytic expression of the model solution as the function with respect to the regularization parameter is obtained. On this basis, we study the method for selecting the regularization parameter through minimizing mean-square error of estimators and obtain the final analytic expression, which resulted in the direct calculation, high processing speed, and adaptability. Finally, the effect of regularization parameter selection on the resolution of point targets is analyzed. The experiment results of simulation and real complex-valued SAR images illustrate the validity of the proposed method.This paper developed a fast and adaptive method for SAR complex image denoising based on lk norm regularization, as viewed from parameters estimation. We firstly establish the relationship between denoising model and ill-posed inverse problem via convex half-quadratic regularization, and compare the difference between the estimator variance obtained from the iterative formula and biased CramerRao bound, which proves the theoretic flaw of the existent methods of parameter selection. Then, the analytic expression of the model solution as the function with respect to the regularization parameter is obtained. On this basis, we study the method for selecting the regularization parameter through minimizing mean-square error of estimators and obtain the final analytic expression, which resulted in the direct calculation, high processing speed, and adaptability. Finally, the effect of regularization parameter selection on the resolution of point targets is analyzed. The experiment results of simulation and real complex-valued SAR images illustrate the validity of the proposed method.

关 键 词：SAR complex-valued image DENOISING lk norm regularization parameters selection fast solution SELF-ADAPTIVE 

分 类 号：TN95[电子电信—信号与信息处理]