基于特征点集的匹配算法应用于卫星姿态确定

综合了灰度与几何特征匹配方法,依据局部纹理能量分布选取特征点集,并利用特征点集的几何约束关系构建了可描述图像整体特征的模板.通过逐步求精方法实现了实时图像与基准图像的匹配.首先通过特征点集匹配进行粗搜索;然后通过精搜索以及角度校正得到实时图像中目标偏移旋转量.该特征点集算法与传统图像匹配算法相比较,在保证精度的基础上能提高匹配速度,且具有一定的旋转不变性和抗噪性.仿真实验证明了该算法的可行性. 

Image matching algorithm based on feature point set for satellite attitude calculation

Gray scale and geometry feature approaches were integrated.Feature point set was selected according to local texture energy distribution and geometry constraint of feature point set was utilized to construct templates describing the holistic feature of the image.A stepped refining image matching algorithm was introduced.Coarse searching was performed first by feature point set registration,thereafter fine searching and angle correction was processed so that the object translation and rotation in the real-time image can be obtained.Compared with traditional image registration methods,this algorithm can enhance the matching speed while maintaining high matching precision with rotation invariance and noise depression capability.The application of such algorithm is verified by simulated experiments.