A matching method for low SNR SAR images

Qingqing Li, Di Zhang, Zhikai Yu, Panhu Li, Jiaqi Li
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Abstract

Aiming at the requirement of high accuracy of synthetic aperture radar (SAR) image matching in scene matching guidance technology, and the problem that traditional matching method is not suitable for low signal to noise ratio (SNR) SAR image, a new SAR image matching method based on Scale-invariant feature transform (SIFT) feature is proposed. Firstly, the enhanced Lee filter is used to pre-process the image, and then the ROEWA is used to assign the main direction and construct the feature vector for SIFT feature points. Finally, the matching result is obtained according to the bidirectional Euclidean distance. The reliability and robustness of the proposed method are verified by comparative simulation.
一种低信噪比SAR图像的匹配方法
针对场景匹配制导技术中合成孔径雷达(SAR)图像匹配精度高的要求,以及传统匹配方法不适合低信噪比SAR图像的问题,提出了一种基于尺度不变特征变换(SIFT)特征的SAR图像匹配新方法。首先使用增强Lee滤波器对图像进行预处理,然后使用ROEWA对SIFT特征点进行主方向分配和特征向量构造。最后,根据双向欧氏距离得到匹配结果。通过对比仿真验证了该方法的可靠性和鲁棒性。
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