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Speckle Filtering of GF-3 Polarimetric SAR Data with Joint Restriction Principle

机译:基于联合约束原理的GF-3极化SAR数据的斑点滤波

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摘要

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.
机译:影像的极化SAR(PolSAR)散射特性始终是从多极化数据的二阶矩估计(即协方差或相干矩阵的估计)获得的。由于从分辨单元内的各个散射体反射的信号必须传播额外的路径,因此散斑噪声始终存在于SAR图像中,并严重影响了散射性能,尤其是对单幅外观复杂的图像。为了获得估计协方差或相干矩阵的高精度,需要考虑三个方面:(1)在斑点滤波后,场景的边缘和纹理是不同的; (2)统计特征应与目标像素相似; (3)除散斑减少外,还应保留偏振散射特征。本文提出了一种联合限制原则来满足这一要求。三种不同的限制原理被引入到斑点滤波的处理中。首先,设计一个更适合于点或线目标的新模板,以确保形态一致性。然后,范围sigma滤波器用于限制上述模板中的像素具有相同的统计特性。最后,将极化相似度因子应用于上述相同像素,以确保可选像素之间具有相似的极化特征。该处理过程被称为具有联合限制原理的斑点滤波,并且该方法应用于在美国加利福尼亚州旧金山获得的GF-3极化SAR数据。通过与Boxcar滤镜和精制Lee滤镜进行比较,验证了其保持图像清晰度和保持散射机制以及减少斑点的有效性。

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