联合属性散射中心的极化目标重构新方法

传统极化目标分解方法将各个像素的散射机理分解为基本散射机理类型的线性加权和，难以反映部件整体结构的极化信息；对于低信噪比的人造复杂目标，直接分解难以反映目标真实的散射特性．通过引入全极化的属性散射中心模型，将目标信号分解为若干典型散射中心的组合以保留结构的整体性；联合极化对属性散射中心进行特征参数提取以降低噪声影响．提出了一种联合属性散射中心的极化目标重构新方法，该算法能很好地从低信噪比的极化数据中对目标信号进行恢复并保持目标典型结构的整体性，有效增强了极化图像的可视性．

Novel polarimetric target signal reconstruction method jointed with attributed scattering centers

Traditional polarimetric target decomposition (PTD) methods decompose the scattering mechanism of every pixel into a weighted sum of basic scattering mechanisms, in which the whole feature of assemblies can hardly be revealed. Moreover, the man-made targets are frequently of low signal-to-noise ratios. Directly applying the PTD methods can hardly reveal the real scattering mechanism of targets. Therefore, the fully polarimetric attributed scattering center model is brought in to decompose the target signal into a set of classical attributed scattering centers to preserve integral properties. Moreover, the parameter is estimated with a high anti-noise property by joint polarization. Based on these, a novel polarimetric target signal reconstruction method jointed with attributed scattering centers is proposed in this paper. The proposed method is capable not only of reconstructing a target signal under low signal-to-noise ratios but also of preserving the integral properties of typical attributed scattering centers. As a result, the visualization of the polarimetric image has been improved effectively.