期刊文献+

微镜头阵列球面排布方法研究 被引量:4

Research of Micro-Ienses Packing Strategy on Spherical Surface
原文传递
导出
摘要 为了解决微镜头阵列在球面上的排布问题,提出了一种通用的基于正二十面体阵列点微移动排布方法。采用与排布球面同心正二十面体点阵投射方法获取微镜头中心点在球面上的初始排布。以弦长率和填充率为评价函数,采用点阵微移动法对此初始结构进行优化。完成方法通用性测试并和一种基于局部球面的经纬线排布法进行对比。实验结果表明,在排布球冠面立体角较大、微相机数量较多的情况下,采用该方法可以获得弦长率低于0.17,填充率达到75%以上的排布表现,同时其良好的排布对称性有效提高了微镜头阵列的成像性能。 An universal perturbed icosahedral projection packing method is presented to solve spherical surface packing problem. First of all, original packing positions is obtained by using icosahedral points projection on its concentric spherical surface. Then, using chord ratio and packing density as merit values, perturbed points moving strategy is used to optimize these initial positions. Finally, universal property of this method is tested by changing the number of packing points. In addition, this method is compared with another packing method, so called hexagonal density packing along longitude and latitude, which is based on local strategy. The result shows that this method is rather effective when the packing solid angle is large and the number of packing lenses is huge, the chord ratio can be reduced below 0.17, and the packing density can be increased above 75%, accompanied with outstanding symmetry, an excellent imaging performance is guaranteed.
出处 《光学学报》 EI CAS CSCD 北大核心 2015年第5期313-320,共8页 Acta Optica Sinica
基金 国家自然科学基金(61170092) 国家自然科学基金重点项目(61133011)
关键词 光学设计 微相机阵列 点阵微移动法 球面排布 填充率 optical design micro-lenses array perturbed points array spherical surface packing packing density
  • 相关文献

参考文献12

二级参考文献84

共引文献117

同被引文献69

  • 1王红梅,张科,李言俊.图像匹配研究进展[J].计算机工程与应用,2004,40(19):42-44. 被引量:107
  • 2黄祝新,徐贵力.仿生复眼测量系统中全景图生成的研究[J].计测技术,2006,26(1):17-20. 被引量:4
  • 3张红鑫,卢振武,王瑞庭,李凤有,刘华,孙强.曲面复眼成像系统的研究[J].光学精密工程,2006,14(3):346-350. 被引量:49
  • 4张红鑫,卢振武,李凤有.人工仿生复眼的研究进展[J].长春理工大学学报(自然科学版),2006,29(2):4-7. 被引量:12
  • 5MARKS D L’LLULL P Kfet al. . Characterization of the AWARE 10 two- gigapixel wide-field-of-view visible imager[ J].Applied Optics ,2014,53( 13) :54-63.
  • 6ZHOU Y L,MEI K Z,et al. . Parallelization and Optimization of SIFT on GPU Using CUDA[ C]. IEEE 15th Internationalconference on high performance computing and communication(HPCC 2013) ,Changsha,China,2013:1351-1358.
  • 7GARCIA V,DEBREUVE E,NIELSEN F,et al. . K-nearest neighbor search:fast GPU-based implementations and applica-tion to high-dimensional feature matching[ C]. IEEE 17th International conference on Image processing,Hong Kong, Chi-na,2010 :3757-3760.
  • 8MUJA M,LOWE D G. Scalable nearest neighbor algorithms for high dimensional data[ J]. IEEE,2014 736( 11 ) :2227-2240.
  • 9GUANG J S,XIANG Y X,YA P D. SIFT feature Point matching based on Improved RANSAC algorithm[ C]. 5th Interna-tional Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC ) , Hangzhou, China ,2013 :474-477.
  • 10徐抒岩.高分辨力空间相机的光学系统研究[J].光学精密工程,2008,16(11):2164-2172. 被引量:81

引证文献4

二级引证文献24

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