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Efficient Registration of Aerial Video to Geo-Referenced Images

机译:航空视频到地理参考图像的有效配准

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Airborne surveillance and reconnaissance play an increasingly crucial role in military operations. Aerial video can perceive dynamic events, track active targets and provide the real-time location of targets, but the poor accuracy of geographical coordinates limits its usefulness. Registration of aerial video to geo-referenced images is an effective means to improve the location accuracy. Generally, the aerial video and the geo-referenced images to be registered were taken at different times, from different viewpoints and by different cameras. Due to these differences, registration of aerial video to geo-referenced images is a challenging task. This paper discusses the essential issues of the problem, analyzes the characteristics of the images, and shows what features work better. Then, this paper presents a two-stage image registration algorithm, which is based on decomposition of transformation space. The first stage estimates the rotation parameter by matching histograms of weighted edge orientation between aerial image and geo-referenced image. The second stage determines the translation parameters by comparing partial images using partial Hausdorff distance. This approach is computationally efficient and robust to significant differences between the images to be aligned. Experiments have been conducted on real-world data, and the results have shown the good performance of the algorithm.
机译:机载监视和侦察在军事行动中起着越来越重要的作用。航拍视频可以感知动态事件,跟踪活动目标并提供目标的实时位置,但是地理坐标的精度差限制了其实用性。航空视频到地理参考图像的配准是提高定位精度的有效手段。通常,要记录的航拍视频和地理参考图像是在不同的时间,从不同的角度和通过不同的相机拍摄的。由于这些差异,将航空视频配准到地理参考图像是一项艰巨的任务。本文讨论了该问题的基本问题,分析了图像的特征,并说明了哪些特征效果更好。然后,提出了一种基于变换空间分解的两阶段图像配准算法。第一阶段通过匹配航空图像和地理参考图像之间的加权边缘方向直方图来估计旋转参数。第二阶段通过使用部分Hausdorff距离比较部分图像来确定平移参数。该方法在计算效率和鲁棒性上要对准的图像之间的显着差异。对真实数据进行了实验,结果表明了该算法的良好性能。

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