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SAR Image Change Detection Algorithm Based on Different Empirical Mode Decomposition

机译:基于不同实证分解的SAR图像改变检测算法

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Empirical mode decomposition (EMD) is a data-driven and multi-scale transform theory, and it is a nonlinear and non-stationary signal processing theory. But each EMD decomposition theory has its advantages and disadvantages. Synthetic aperture radar (SAR) imaging is an important remote sensing technique to obtain the change information, and SAR image data belongs to non-stationary signal. So EMD is very suitable for SAR image processing. There are two kinds of typical EMD theories, which are the ensemble empirical mode decomposition (EEMD) and bidimensional empirical mode decomposition (BEMD). Based on the deep study of the two methods, this paper proposed a new SAR image change detection algorithm, which is called the FCD-EMD algorithm, i.e. fusion change detection based on EMD. So FCD-EMD algorithm can obtain more accurate information, which not only includes the directional information obtained by EEMD, but also can contain the spatial information got by BEMD. The main contribution of the FCD-EMD algorithm is to fuse the detail information in different directions, so that the results obtained are more accurate than the individual method. On the other hand, it can reduce the influence of speckle noise in SAR images by feature selections. The actual SAR image data verify the algorithm proposed in this paper and good experimental results are obtained, which show that the new method is feasible.
机译:经验模式分解(EMD)是一种数据驱动和多尺度变换理论,它是非线性和非静止信号处理理论。但每个EMD分解理论都有其优缺点。合成孔径雷达(SAR)成像是一种重要的遥感技术,可以获得更改信息,并且SAR图像数据属于非稳定性信号。因此EMD非常适合SAR图像处理。有两种典型的EMD理论,这是集合经验模式分解(EEMD)和均衡经验模式分解(BEMD)。基于两种方法的深度研究,本文提出了一种新的SAR图像改变检测算法,称为FCD-EMD算法,即基于EMD的融合变化检测。因此,FCD-EMD算法可以获得更准确的信息,这不仅包括通过EEMD获得的方向信息,而且还可以包含BEMD获得的空间信息。 FCD-EMD算法的主要贡献是融合不同方向的详细信息,从而获得的结果比单个方法更准确。另一方面,它可以通过特征选择减少SAR图像中的斑点噪声的影响。实际的SAR图像数据验证了本文提出的算法,获得了良好的实验结果,这表明新方法是可行的。

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