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基于SURF算法的无人机航空图像自动配准研究
引用本文:李二俊,刘万林,余涛,谢东海,蔡庆空.基于SURF算法的无人机航空图像自动配准研究[J].工程勘察,2013(10):49-52,57.
作者姓名:李二俊  刘万林  余涛  谢东海  蔡庆空
作者单位:[1]长安大学地质工程与测绘学院,西安710054 [2]中国科学院遥感应用研究所,北京100101 [3]中国矿业大学(北京)地球科学与测绘工程学院,北京100083
基金项目:国家973计划项目(Y070070070);中科院战略先导专项子课题(Y1Y02230XD);中科院创新项目(09Y01500KB).
摘    要:针对实时性要求中SIFT特征配准算法耗时长的缺点,本文将SURF(Speeded Up Robust Feature,即加速鲁棒特征)算法应用于无人机航空图像的自动配准问题中。首先利用Hessian检测子检测特征点,再通过粗匹配和细匹配得到匹配点对,最后执行几何变换完成对图像的配准。通过与SIFT(Scale Invariant Feature Transform,即尺度不变特征变换)配准方法进行对比,结果表明SURF算法在满足精度的前提下具有比SIFT算法计算量小、速度快的优点,有一定的理论和应用价值。

关 键 词:SURF算法  图像配准  Hessian检测子  几何变换  SIFT算法

Automatic registration of unmanned aerial vehicle images based on SURF operator
Li Erjun,Liu Wanlinl,Yu Tao,Xie Donghaiz,Cai Qingkong.Automatic registration of unmanned aerial vehicle images based on SURF operator[J].Geotechnical Investigation & Surveying,2013(10):49-52,57.
Authors:Li Erjun  Liu Wanlinl  Yu Tao  Xie Donghaiz  Cai Qingkong
Affiliation:3 ( 1. School of Geology Engineering and Geomatics , Chang' an University, Xi' an 710054, China ; 2. Institute of Remote Sensing and Applications, Chinese Academy of Sciences, Beijing 100101, China ; 3. College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, China)
Abstract:To overcome the shortcoming of SIFT registration algorithm, SURF operator is introduced into automatic registration of UAV aerial images. Firstly, the feature points are extracted through the Hessian detector. Secondly, matched points are selected through the coarse matching and the fine matching. Finally, the geometry transform is taken to complete the registration. An real experiment is performed, in which the proposed method is compared with the automatic registration method based on SIFT. The results show that SURF method meets the needs of accuracy and is faster than SIFT as well. So, our new method is valuable in both theory and practice.
Keywords:SURF algorithm  image registration  Hessian detector  geometry transform  SIFT algorithm
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