National Laboratory of Radar Signal Processing, Xidian University, Xi'an 710071, China.
Beijing Institute of Spacecraft System Engineering, China Academy of Space Technology, Beijing 100094, China.
Sensors (Basel). 2018 May 12;18(5):1533. doi: 10.3390/s18051533.
Polarimetric SAR (PolSAR) scattering characteristics of imagery are always obtained from the second order moments estimation of multi-polarization data, that is, the estimation of covariance or coherency matrices. Due to the extra-paths that signal reflected from separate scatterers within the resolution cell has to travel, speckle noise always exists in SAR images and has a severe impact on the scattering performance, especially on single look complex images. In order to achieve high accuracy in estimating covariance or coherency matrices, three aspects are taken into consideration: (1) the edges and texture of the scene are distinct after speckle filtering; (2) the statistical characteristic should be similar to the object pixel; and (3) the polarimetric scattering signature should be preserved, in addition to speckle reduction. In this paper, a joint restriction principle is proposed to meet the requirement. Three different restriction principles are introduced to the processing of speckle filtering. First, a new template, which is more suitable for the point or line targets, is designed to ensure the morphological consistency. Then, the extent sigma filter is used to restrict the pixels in the template aforementioned to have an identical statistic characteristic. At last, a polarimetric similarity factor is applied to the same pixels above, to guarantee the similar polarimetric features amongst the optional pixels. This processing procedure is named as speckle filtering with joint restriction principle and the approach is applied to GF-3 polarimetric SAR data acquired in San Francisco, CA, USA. Its effectiveness of keeping the image sharpness and preserving the scattering mechanism as well as speckle reduction is validated by the comparison with boxcar filters and refined Lee filter.
极化合成孔径雷达（PolSAR）图像的散射特性通常是通过多极化数据的二阶矩估计获得的，即协方差或相干矩阵的估计。由于信号从分辨单元内的不同散射体反射时必须经过额外的路径，因此 SAR 图像中总是存在斑点噪声，这对散射特性，尤其是对单视复数图像，有严重的影响。为了实现协方差或相干矩阵的高精度估计，需要考虑以下三个方面：（1）斑点滤波后，场景的边缘和纹理清晰；（2）统计特性应与目标像素相似；（3）除了减少斑点外，还应保留极化散射特征。本文提出了一种联合约束原理来满足这一要求。将三种不同的约束原理引入到斑点滤波处理中。首先，设计了一种更适合点或线目标的新模板，以确保形态一致性。然后，使用扩展 sigma 滤波器限制模板中像素的统计特性相同。最后，对上述相同像素应用极化相似性因子，以保证可选像素之间具有相似的极化特征。该处理过程称为基于联合约束原理的斑点滤波，将该方法应用于美国加利福尼亚州旧金山获取的 GF-3 极化 SAR 数据。通过与盒式滤波器和改进的 Lee 滤波器的比较，验证了该方法在保持图像锐度和保留散射机制以及减少斑点方面的有效性。
