Feature point set image matching algorithm for satellite attitude determination

Xiaodong Cai, Peijian Ye
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Abstract

This paper constructs a template for description of global image feature by integrating matching methods of grayscale and geometry feature, selecting feature point set depending on partial texture energy distribution and utilizing geometrical constraints among points. The matching between real-time image and reference image is realized through stepwise refinement method. The first step is a coarse search by feature point set matching. Fine registrations include cluster analysis and close object matching. Compared with traditional image matching algorithm, feature point set algorithm can improve matching speed and closed object matching can meet the precision requirement. Its practicability has been proved by simulated experiments
卫星姿态确定的特征点集图像匹配算法
结合灰度和几何特征的匹配方法,根据部分纹理能量分布选择特征点集,利用点间的几何约束,构建图像全局特征描述模板。通过逐步细化的方法实现实时图像与参考图像的匹配。第一步是通过特征点集匹配进行粗搜索。精细配准包括聚类分析和接近目标匹配。与传统的图像匹配算法相比,特征点集算法可以提高匹配速度,封闭目标匹配可以满足精度要求。仿真实验证明了该方法的实用性
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