一种地外天体路标图像的稀疏化表征方法

A Sparse Descriptor for Landmarks of Extraterrestrial Celestial Bodies

针对用于地外天体着陆视觉导航的路标图像信息存在的计算量大和占用存储空间大等问题,提出一种路标图像的稀疏化表征方法.引入着陆路标图像的尺度估计和尺度变换,采用Harris算法提取路标特征点,改进了FREAK特征描述子用以稀疏化表征天体路标信息;并针对图像旋转、尺度变化、图像噪声和尺度估计误差4种外界干扰,仿真对比改进算法与原FREAK算法、SURF算法的性能.仿真结果表明:提出的算法大幅减少计算量和特征描述子所占用的存储空间,同时能够正确匹配到更多的路标特征,鲁棒性更好,更适合地外天体着陆任务应用.

Focusing on the problems of computational burden and shortage of storage space for visual navigation in extraterrestrial body landing missions,a sparse descriptor for landmarks is proposed in this paper. The scale prediction and scale transformation of descent images are introduced,and the image features are extracted based on Harris algorithm,and FREAK algorithm is improved to descript the image features. Finally,the performances of the proposed algorithm,FREAK algorithm and SURF algorithm are compared under four external disturbances. The simulation results show that the proposed algorithm greatly reduces computational burden and demand for storage space,and is more suitable for landing missions of extraterrestrial objects.