SAR复图像域上的噪声抑制和目标特征提取

The Noise-Suppression and Feature-Extraction in SAR Complex-Imagery Domain

基于SAR图像的稀疏先验,提出了一种基于lk范数的复图像域正则化方法,用于SAR复图像的噪声抑制和目标特征提取.文中通过算法设计及其收敛性的研究,保证了该方法的可行性和稳健性.同时,基于正则化方法与广义岭估计的契合之处,提出了一种新的正则化参数的选取方法.理论分析和实验结果均表明,本文方法可操作性强,具有有效的噪声抑制和目标特征稀疏表示寻优功能.

For the noise suppression and target＇s feature-extraction of the synthetic aperture radar （SAR） imagery in complex domain, a regularization method based on lk norm is presented in SAR complex imagery domain in terms of the sparse prior of SAR imagery. The design of the algorithm and the research on its convergence assure the feasibility and robustness of this method. The coupling between the regularizafion method and ridge estimate afford a new idea of the choice of the regularization parameters. Numerical results demonstrate that our method can efficiently depress noise and extract the target＇s feature of SAR image.