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A New Synthetic Aperture Radar (SAR) Imaging Method Combining Match Filter Imaging and Image Edge Enhancement

机译:结合匹配滤波器成像和图像边缘增强的合成孔径雷达(SAR)成像新方法

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摘要

In general, synthetic aperture radar (SAR) imaging and image processing are two sequential steps in SAR image processing. Due to the large size of SAR images, most image processing algorithms require image segmentation before processing. However, the existence of speckle noise in SAR images, as well as poor contrast and the uneven distribution of gray values in the same target, make SAR images difficult to segment. In order to facilitate the subsequent processing of SAR images, this paper proposes a new method that combines the back-projection algorithm (BPA) and a first-order gradient operator to enhance the edges of SAR images to overcome image segmentation problems. For complex-valued signals, the gradient operator was applied directly to the imaging process. The experimental results of simulated images and real images validate our proposed method. For the simulated scene, the supervised image segmentation evaluation indexes of our method have more than 1.18%, 11.2% and 11.72% improvement on probabilistic Rand index (PRI), variability index (VI), and global consistency error (GCE). The proposed imaging method will make SAR image segmentation and related applications easier.
机译:通常,合成孔径雷达(SAR)成像和图像处理是SAR图像处理中的两个连续步骤。由于SAR图像的大小很大,因此大多数图像处理算法都需要在处理之前对图像进行分割。但是,SAR图像中存在斑点噪声,以及在同一目标中对比度差和灰度值分布不均,使得SAR图像难以分割。为了方便SAR图像的后续处理,本文提出了一种结合反投影算法(BPA)和一阶梯度算子来增强SAR图像边缘以克服图像分割问题的新方法。对于复数值信号,将梯度算子直接应用于成像过程。仿真图像和真实图像的实验结果验证了我们提出的方法。对于模拟场景,我们方法的监督图像分割评估指标在概率兰德指数(PRI),变异性指数(VI)和全局一致性误差(GCE)方面分别提高了1.18%,11.2%和11.72%。提出的成像方法将使SAR图像分割和相关应用更加容易。

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