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关昭, 乔卫东, 杨建峰, 薛彬, 陶金有. 火星多光谱相机的地面几何标定研究[J]. 深空探测学报(中英文), 2018, 5(5): 465-471. DOI: 10.15982/j.issn.2095-7777.2018.05.009
引用本文: 关昭, 乔卫东, 杨建峰, 薛彬, 陶金有. 火星多光谱相机的地面几何标定研究[J]. 深空探测学报(中英文), 2018, 5(5): 465-471. DOI: 10.15982/j.issn.2095-7777.2018.05.009
GUAN Zhao, QIAO Weidong, YANG Jianfeng, XUE Bin, TAO Jinyou. Ground Geometric Calibration of Mars Multispectral Camera[J]. Journal of Deep Space Exploration, 2018, 5(5): 465-471. DOI: 10.15982/j.issn.2095-7777.2018.05.009
Citation: GUAN Zhao, QIAO Weidong, YANG Jianfeng, XUE Bin, TAO Jinyou. Ground Geometric Calibration of Mars Multispectral Camera[J]. Journal of Deep Space Exploration, 2018, 5(5): 465-471. DOI: 10.15982/j.issn.2095-7777.2018.05.009

火星多光谱相机的地面几何标定研究

Ground Geometric Calibration of Mars Multispectral Camera

  • 摘要: 随着航空航天技术的飞速发展,作为地球近邻的火星成为当今国际空间大国的主要研究目标。为完成火星巡视区形貌和地质探测任务,可直接使用多光谱相机获取的高分辨率真彩色图像作为观测手段。为寻找着陆点,火星多光谱相机应具备精确定位的测绘功能,因此需进行几何标定估计其内方位元素。通过张正友标定算法提供初值,然后以改进的Heikkilä算法完成几何标定,经过分析标定结果的不确定度,探究实验误差来源,提出改进方法,最终获得满足要求的标定参数,为实现图像融合、三维重建等计算机视觉领域奠定坚实的基础。

     

    Abstract: With the rapid development of aerospace technology, as the near neighbor of the Earth, the Mars has become the main research target of the leading space power in the world. To complete the Mars patrolling area topography and geological exploration missions, true color images with high resolution obtained by multispectral cameras can be used directly as observations. In order to find the landing point, the Mars multispectral camera should possess the mapping function with precise positions, so it is necessary to conduct the geometric calibration for measuring intrinsic elements. The Zhang Zhengyou calibration algorithm is used to provide initial values, and then combined with the improved Heikkilä algorithm in this paper. After analyzing the uncertainty of the calibration results, and finding out the source of experimental errors, an improved method for calibration parameters is proposed to meet the requiremens, which lays a solid foundation for 3D reconstruction and other fields of computer vision.

     

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