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基于点特征和边缘特征的无人机影像配准方法

何敬 李永树 李歆 唐敏

何敬, 李永树, 李歆, 唐敏. 基于点特征和边缘特征的无人机影像配准方法[J]. 西南交通大学学报, 2012, 25(6): 955-961. doi: 10.3969/j.issn.0258-2724.2012.06.008
引用本文: 何敬, 李永树, 李歆, 唐敏. 基于点特征和边缘特征的无人机影像配准方法[J]. 西南交通大学学报, 2012, 25(6): 955-961. doi: 10.3969/j.issn.0258-2724.2012.06.008
HE Jing, LI Yongshu, LI Xin, TANG Min. Registration Method for Unmanned Aerial Vehicle Images Based on Point Feature and Edge Feature[J]. Journal of Southwest Jiaotong University, 2012, 25(6): 955-961. doi: 10.3969/j.issn.0258-2724.2012.06.008
Citation: HE Jing, LI Yongshu, LI Xin, TANG Min. Registration Method for Unmanned Aerial Vehicle Images Based on Point Feature and Edge Feature[J]. Journal of Southwest Jiaotong University, 2012, 25(6): 955-961. doi: 10.3969/j.issn.0258-2724.2012.06.008

基于点特征和边缘特征的无人机影像配准方法

doi: 10.3969/j.issn.0258-2724.2012.06.008
基金项目: 

"十一五"国家科技支撑计划重大项目(2006BAJ05A13)

Registration Method for Unmanned Aerial Vehicle Images Based on Point Feature and Edge Feature

  • 摘要: 为解决变形较大的无人机影像配准问题,提出了点特征和边缘特征相结合的配准方法.用尺度不变特征变换(SIFT)算法提取点特征,完成影像的初步配准,并通过多项式函数对影像进行粗校正.在此基础上提取影像的边缘特征信息,根据距离相似性对边缘特征信息进行配准;依据色彩能量差筛选点特征信息配准结果和边缘特征信息配准结果,采用小面元微分校正的方法对变形影像进行校正.实验结果表明:提出的配准方法能够弥补点特征配准方法和边缘特征配准方法的不足,其配准的鲁棒性提高10%左右,可以较好地完成变形较大的无人机影像配准.

     

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出版历程
  • 收稿日期:  2012-04-06
  • 刊出日期:  2012-12-25

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