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Ship Detection for High-Resolution SAR Images Based on Feature Analysis

机译:基于特征分析的高分辨率SAR图像舰船检测

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High-resolution synthetic aperture radar (SAR) data have been widely used in marine environmental protection, marine environmental monitoring, and marine traffic management. Ship detection is one of the important parts of SAR data for marine applications. This letter focuses on the feature analysis of ships in high-resolution SAR images and proposes an improved optimizing algorithm for ship detection. A fast block detector is designed to extract sea clutter in a uniform local area, and then a constant false alarm rate detector is employed. Based on the kernel density estimation of ships, aspect ratio, and pixel points, ships are identified. TerraSAR-X and COSMO-SkyMed images are used to test our algorithm. The experimental results show that this algorithm can be implemented with time-saving, high-precision ship extraction, feature analysis, and detection.
机译:高分辨率合成孔径雷达(SAR)数据已广泛用于海洋环境保护,海洋环境监测和海洋交通管理。船舶检测是用于海洋应用的SAR数据的重要部分之一。这封信着重于高分辨率SAR图像中船舶的特征分析,并提出了一种改进的船舶检测优化算法。设计了一种快速阻塞探测器,以在均匀的局部区域提取海浪杂波,然后使用恒定的误报率探测器。基于船只的核密度估计,宽高比和像素点,可以确定船只。 TerraSAR-X和COSMO-SkyMed图像用于测试我们的算法。实验结果表明,该算法可实现省时,高精度的船舶提取,特征分析和检测。

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