Journal of Marine Science and Technology

, Volume 21, Issue 1, pp 38–47 | Cite as

A feature-matching method for side-scan sonar images based on nonlinear scale space

  • Xiu-Fen Ye
  • Peng Li
  • Jian-Guo Zhang
  • Jian Shi
  • Shu-Xiang Guo
Original article

Abstract

We report a novel feature-matching method for side-scan sonar images. The method uses nonlinear diffusion filtering to build a nonlinear scale space. The noise-reduction performance is enhanced via nonlinear diffusion filtering, and the improved Perona–Malik diffusion equation results in a more distinct edge and line texture in the side-scan sonar image. The modified feature descriptor reduces the dimensionality of the feature vector so that the computational expense is reduced. Experimental results show that the method provides improved noise-reduction performance and better accuracy than SIFT, SURF, and other state-of-the-art feature-matching algorithms.

Keywords

Feature matching Side-scan sonar image Nonlinear scale spaces 

Notes

Acknowledgments

This research was supported by Natural Science Foundation of Heilongjiang Province of China (Grant No. F201416) and National Natural Science Foundation of China (Grant No. 61375094).

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Copyright information

© JASNAOE 2015

Authors and Affiliations

  • Xiu-Fen Ye
    • 1
  • Peng Li
    • 1
  • Jian-Guo Zhang
    • 1
  • Jian Shi
    • 1
  • Shu-Xiang Guo
    • 1
    • 2
  1. 1.College of AutomationHarbin Engineering UniversityHarbinPeople’s Republic of China
  2. 2.Faculty of EngineeringKagawa UniversityHayashichouJapan

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