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Aircraft Target Detection Algorithm Based on High Resolution Spaceborne SAR Imagery

机译:基于高分辨率的飞机目标检测算法SAR图像

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摘要

In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.
机译:本文提出了一种基于合成孔径雷达(SAR)图像的统计特征和像素的空间信息的机场区域的图像分类算法。该算法结合了伽马混合物模型和MRF。使用伽马混合模型获得初始分类结果的算法。基于分类结果的像素空间相关由MRF技术进行了优化。另外,使用形态学方法来提取机场(ROI)区域,其中澄清了疑似飞机目标样品以减少误报并提高检测性能。最后,本文提出了通过仿真测试验证的平面​​目标检测。

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