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A Reliable Matching Algorithm Based on the Rational Function Model Bundle Adjustment for Satellite Imagery

机译:一种可靠的匹配算法基于卫星图像Rational函数模型捆绑调整的可靠匹配算法

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Aim to the practical problem of high-resolution imagery automatic matching, the paper proposes a reliable matching algorithm based on the rational function model bundle adjustment, the basic idea of which is the introduction of the rational function model bundle adjustment to the pyramid image matching, this will establish the geometric relationship between images, and realize the accurate prediction of matching points' initial position, fast matching with epipolar line constrained and rough geometric correction, and the elimination of error matching points. Refine matching layer by layer, and finally using the least squares matching algorithm to obtain the matching result of the sub-pixel level. Experiment has been made on the World View satellite imagery of Qinghai province in China, and it has shown that the method proposed in this paper can effectively overcome the impact of image radiation distortion, image rotation and some geometric deformation and so on, achieving the automatic and reliable conjugate point matching of satellite remote sensing imagery.
机译:旨在实现高分辨率图像自动匹配的实际问题,提出了一种基于Rational Function Model捆绑调整的可靠匹配算法,其基本思想是将Rational函数模型束调节引入金字塔图像匹配的基本思想,这将建立图像之间的几何关系,并实现匹配点的准确预测匹配点的初始位置,与末极线约束和粗糙几何校正的快速匹配,以及消除误差匹配点。通过层进行精制匹配层,最后使用最小二乘匹配算法来获得子像素级别的匹配结果。在中国青海省卫星图像上进行了实验,并表明本文提出的方法可以有效地克服图像辐射失真,图像旋转和一些几何变形等的影响,实现自动卫星遥感图像的可靠共轭点匹配。

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