A Performance Evaluation of SIFT and SURF for Multispectral Image Matching

  • Sajid Saleem
  • Abdul Bais
  • Robert Sablatnig
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7324)


This paper evaluates the performance of SIFT and SURF for cross band matching of multispectral images. The evaluation is based on matching a reference spectral image with the images acquired at different spectral bands. The reference image possesses scale and (in-plane) rotational differences in addition to spectral variations. Additive white Gaussian noise is also added to compare performance degradation at different noise levels. We use the precision and repeatability criteria for performance evaluation. Experimental results demonstrate that SIFT performs better than SURF in multispectral environment.


SIFT SURF multispectral images cross band image matching 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Sajid Saleem
    • 1
  • Abdul Bais
    • 2
  • Robert Sablatnig
    • 1
  1. 1.Computer Vision LabInstitute of Computer Aided Automation, Vienna University of TechnologyViennaAustria
  2. 2.Faculty of Engineering and Applied ScienceUniversity of ReginaReginaCanada

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