期刊文献+

嫦娥一号月面成像的高精度匹配及月貌三维重建 被引量:8

High Precision Matching and 3DSurface Reconstruction of Chang′E 1 Lunar Images
原文传递
导出
摘要 针对嫦娥一号探月卫星2C级月面成像,提出了基于待配点最优模板选择的二次函数形变补偿迭代匹配方法。仿真表明它能有效地适应地形起伏引起的图像形变,匹配精度较高且稳定性好。在标准相关匹配的基础上结合所提出的方法完成了下视图与前、后视图的精确匹配,采用三视约束机制和顺序检验机制保证了匹配的稳健性。分析了线阵相机成像的仿射近似模型,并以此为基础实现同轨三视重建。基于邻轨下视图同名特征点,采用RANSAC方法估计邻轨三维坐标转换参数,完成邻轨拼接。实验结果表明,三维重建的月貌图能够更好地表达月球表面的形状和地形。 An iterative matching method based on choosing optimal mask and representing deformation by the quadric function is proposed to solve the matching problem of 2C level lunar images by Chang^E 1 (CE1) lunar probe satellite. The simulation results show that it has high precision and stability which self adapts well to the relief terrain's imaging deformation. A precise matching is applied to the normal view, forward view and backward view of the CE1 image by combining the proposed method and the standard correlation method. Mfine model approximating the imaging of line scanner camera is analyzed and applied to the same orbit's three-view reconstruction. The adjacent orbit's lunar terrain registration is realized by RANSAC estimation of three-dimensional (3D) coordinate transformation parameters led by matching feature points of adjacent normal views. The experiment results indicate that the shape and terrain of lunar surface can be better understood from the reconstructed results.
出处 《光学学报》 EI CAS CSCD 北大核心 2014年第2期84-92,共9页 Acta Optica Sinica
基金 国家973计划(2013CB733100)
关键词 图像处理 三维重建 图像匹配 三线阵CCD 二次函数形变 嫦娥一号 月面图像 image processing three-dimensional reconstruction image matching three-line-scanner quadric function deformation ChangrE 1 lunar image
  • 相关文献

参考文献14

二级参考文献134

共引文献126

同被引文献107

  • 1隋婧,金伟其.双目立体视觉技术的实现及其进展[J].电子技术应用,2004,30(10):4-6. 被引量:87
  • 2王向军,王研,李智.基于特征角点的目标跟踪和快速识别算法研究[J].光学学报,2007,27(2):360-364. 被引量:48
  • 3王鲲鹏,张小虎,李立春,于起峰.一种基于正负差图像的运动目标检测新方法[J].应用光学,2007,28(5):521-525. 被引量:11
  • 4LIN Y M, LU N G, LOU X P, et al.. Matching cost filtering for dense stereo correspondence [J]. Mathematical Problems in Engineering, 2013, 2013,654139-11.
  • 5ZHOU Z, LIU N, WU D, et al.. Stereo matching based on adaptive window and reliability constraint [J]. Journal of Computational Information Sys-tems, 2013,9(16), 6669-6675.
  • 6FREEDMAN B, SHPUNT A, MACHLINE M, et al.. Depth mapping using projected patterns, US 8150142B2, 2012[P].
  • 7SUN Y, PANG j H L. Study of optimal subset size in digital image correlation of speckle pattern images[J]. Optics and Lasers in Engineering, 2007, 45(9): 967-974.
  • 8PANB, XIE H M, WANG ZH Y, etal.. Study on subset size selection in digital image correlation for speckle patterns[J]. Optics Eccpress, 2008, 16 (10): 7037-7048.
  • 9VIOLA P, JONES M. Rapid object detection u- sing a boosted cascade of simple features[C]. Computer Vision and Pattern Recognition, 2001, 1: 511-518.
  • 10Saxena A, Schulte J, Ng A Y. Depth estimation using monocular and stereo cues [C]. Proceeding of 20th International Joint Conference on Artificial Intelligence Organization (IJCAI), 2007: 2197-2203.

引证文献8

二级引证文献91

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部