3D Research

, 9:52 | Cite as

Feature Matching Improvement through Merging Features for Remote Sensing Imagery

  • Shahid KarimEmail author
  • Ye Zhang
  • Ali Anwar Brohi
  • Muhammad Rizwan Asif
3DR Express
Part of the following topical collections:
  1. Object detection and Recognition


Feature matching is the core stage for object recognition, tracking and several applications of computer vision. Low resolution images have various limitations with respect to spatial, spectral, pixel and temporal information which reduces the performance of image processing approaches. We have combined SURF features with FAST and BRISK features individually in order to provide an optimal solution for feature matching. Furthermore, feature matching has exploited through combined features and compared the performance with state-of-the-art methods. Lastly, RANSAC and MSAC were utilized to eliminate the wrong matches to get optimal feature matches. The experimental results show that the combination of FAST–SURF and BRISK–SURF perform feature matching optimally according to the number of feature matches and estimated time.


Feature matching SURF FAST BRISK RANSAC 



This work was supported by the National Natural Science Foundation of China under Grants 61471148.


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Copyright information

© 3D Research Center, Kwangwoon University and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Shahid Karim
    • 1
    Email author
  • Ye Zhang
    • 1
  • Ali Anwar Brohi
    • 2
  • Muhammad Rizwan Asif
    • 3
  1. 1.School of Electronics and Information EngineeringHarbin Institute of TechnologyHarbinChina
  2. 2.School of Energy Science and EngineeringHarbin Institute of TechnologyHarbinChina
  3. 3.School of Electronics and Information EngineeringXi’an Jiaotong UniversityXi’anChina

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