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Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map

机译:基于梯度纹理显着图的高分辨率SAR图像中的飞机检测

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摘要

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate.
机译:本文提出了一种新的自动和自适应飞机目标检测算法,用于机场的高分辨率合成孔径雷达(SAR)图像中。该方法基于围裙区域上下文提示下的梯度纹理显着图。首先,从停机坪区域中检测可能存在机场的候选区域。其次,使用定向局部梯度分布检测器来获得有利于候选区域的梯度纹理显着图。另外,将通过使用CFAR型算法对显着性图进行分段来检测最终目标。真实的高分辨率机载SAR图像数据用于验证所提出的算法。结果表明,该算法可以快速,准确地检测出飞机目标,降低了误报率。

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