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Methods of orientating different Resolution Satellite Images with the existing Vector Maps

机译:用现有矢量地图定位不同分辨率卫星图像的方法

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In this paper, the different methods of orientating different resolution satellite images with the existing vector maps are introduced. To moderate high resolution satellite image, such as SPOT5 image, the vector road maps are often used for the orientation, and the vector lines in the maps usually represent the road central lines. And to higher resolution satellite image, such as QuickBird image, the vector lines in the maps usually represent the road edges, instead. Beside that, the different extend of details of the images makes it necessary to handle them with different methods. Because in very high resolution satellite images a lot of disturbing image features will be extracted along with the wanted one. A voting algorithm is employed to solve the problem, the approach is based on the previous work where an edge-based voting strategy was studied1. The voting algorithm has the advantages of globally optimal and robust to noise. It can directly estimate the transformation parameters, meanwhile providing the potential matches of edge points, these matches can then be used in calculating the accurate orientation parameters, and providing the chance of change detection since the unchanged objects can be marked out with this method.
机译:在本文中,介绍了使用现有矢量地图定位不同分辨率卫星图像的不同方法。为了调节高分辨率的卫星图像(例如SPOT5图像),通常使用矢量道路图作为方向,并且地图中的矢量线通常代表道路中心线。对于高分辨率卫星图像(例如QuickBird图像),地图中的矢量线通常代表道路边缘。除此之外,图像细节的不同扩展使得有必要使用不同的方法来处理它们。因为在非常高分辨率的卫星图像中,许多干扰的图像特征将与所需的特征一起被提取。投票算法被用来解决这个问题,该方法基于以前的工作,在该工作中研究了基于边缘的投票策略。投票算法具有全局最优和抗噪声的优点。它可以直接估计变换参数,同时提供边缘点的潜在匹配,这些匹配可用于计算准确的方向参数,并提供检测变化的机会,因为可以用此方法标记出未改变的对象。

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