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A New SAR Image Segmentation Algorithm for the Detection of Target and Shadow Regions

机译:一种新的SAR图像分割和目标阴影区域检测算法

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The most distinctive characteristic of synthetic aperture radar (SAR) is that it can acquire data under all weather conditions and at all times. However, its coherent imaging mechanism introduces a great deal of speckle noise into SAR images, which makes the segmentation of target and shadow regions in SAR images very difficult. This paper proposes a new SAR image segmentation method based on wavelet decomposition and a constant false alarm rate (WD-CFAR). The WD-CFAR algorithm not only is insensitive to the speckle noise in SAR images but also can segment target and shadow regions simultaneously, and it is also able to effectively segment SAR images with a low signal-to-clutter ratio (SCR). Experiments were performed to assess the performance of the new algorithm on various SAR images. The experimental results show that the proposed method is effective and feasible and possesses good characteristics for general application.
机译:合成孔径雷达(SAR)最鲜明的特点是,它可以在所有天气条件下随时随地获取数据。然而,其相干成像机制将大量斑点噪声引入到SAR图像中,这使得SAR图像中目标区域和阴影区域的分割非常困难。提出了一种基于小波分解和恒定误报率(WD-CFAR)的SAR图像分割新方法。 WD-CFAR算法不仅对SAR图像中的斑点噪声不敏感,而且可以同时分割目标区域和阴影区域,并且还能够有效地以低信噪比(SCR)分割SAR图像。实验进行了评估新算法在各种SAR图像上的性能。实验结果表明,该方法有效可行,具有良好的通用性。

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