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Multi-sensor Image Registration for Precisely Locating Time-sensitive Objects

机译:精确定位时间敏感对象的多传感器图像配准

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Finding time-sensitive objects in time and precisely locating them in real time is the basis of successful operations. This paper analyzes the characteristics of images from space-based platforms such as satellites, and images from aerial platforms such as UAVs, and then presents a method for precisely locating time-sensitive targets. The idea behind this method is that, because the satellite images from intelligence image database have accurate geodetic coordinates associated with every pixel, aerial images can obtain the geographical coordinates of high accuracy by registration with the satellite images. The key of this method consists in alignment of the two kinds of images. To do so, this paper presents a two-stage image registration algorithm. The first stage performs image stitching for aerial images so that the resulting images can include more structural information of the scene. In the second stage, the resulting images are aligned with the geo-referenced images from the image intelligence database. Experimental results show that the proposed algorithm is effective and robust in case of scene variations.
机译:及时找到对时间敏感的对象并对其进行实时精确定位是成功操作的基础。本文分析了来自卫星等天基平台的图像和来自无人机等空中平台的图像的特征,然后提出了一种精确定位时间敏感目标的方法。该方法背后的思想是,由于来自智能图像数据库的卫星图像具有与每个像素关联的准确的大地坐标,因此航空图像可以通过与卫星图像配准来获得高精度的地理坐标。该方法的关键在于两种图像的对齐。为此,本文提出了一种两阶段的图像配准算法。第一阶段对航空图像执行图像拼接,以使生成的图像可以包含场景的更多结构信息。在第二阶段中,将所得图像与来自图像智能数据库的地理参考图像对齐。实验结果表明,该算法在场景变化的情况下是有效且鲁棒的。

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