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Multitemporal SAR Image Despeckling Based on a Scattering Covariance Matrix of Image Patch

机译:基于图像补丁散射协方差矩阵的多时相SAR图像去斑

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摘要

This paper presents a despeckling method for multitemporal images acquired by synthetic aperture radar (SAR) sensors. The proposed method uses a scattering covariance matrix of each image patch as the basic processing unit, which can exploit both the amplitude information of each pixel and the phase difference between any two pixels in a patch. The proposed filtering framework consists of four main steps: (1) a prefiltering result of each image is obtained by a nonlocal weighted average using only the information of the corresponding time phase; (2) an adaptively temporal linear filter is employed to further suppress the speckle; (3) the final output of each patch is obtained by a guided filter using both the original speckled data and the filtering result of step 3; and (4) an aggregation step is used to tackle the multiple estimations problem for each pixel. The despeckling experiments conducted on both simulated and real multitemporal SAR datasets reveal the pleasing performance of the proposed method in both suppressing speckle and retaining details, when compared with both advanced single-temporal and multitemporal SAR despeckling techniques.
机译:本文提出了一种合成孔径雷达(SAR)传感器获取的多时相图像去斑点方法。所提出的方法使用每个图像补丁的散射协方差矩阵作为基本处理单元,它可以利用每个像素的幅度信息和补丁中任何两个像素之间的相位差。所提出的滤波框架包括四个主要步骤:(1)通过仅使用相应时相的信息通过非局部加权平均值获得每个图像的预滤波结果; (2)采用自适应时间线性滤波器进一步抑制斑点。 (3)每个斑块的最终输出是由导引滤波器使用原始斑点数据和步骤3的滤波结果获得的; (4)使用聚合步骤来解决每个像素的多重估计问题。与先进的单时相和多时相SAR去斑技术相比,在模拟和实际多时相SAR数据集上进行的去斑实验表明,该方法在抑制斑点和保留细节方面表现出令人满意的性能。

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