Signal, Image and Video Processing

, Volume 12, Issue 7, pp 1237–1244 | Cite as

The multiscale directional neighborhood filter and its application to clutter removal in GPR data

  • D. Kumlu
  • I. Erer
Original Paper


We present a novel neighborhood filter (NF)-based clutter removal algorithm in ground-penetrating radar (GPR) images. Since NF uses only range kernel of the well-known bilateral filter, it is less complex and makes clutter removal method appropriate for real-time implementations. We extend NF to multiscale–multidirectional case: MDNF and then decompose the GPR image into approximation and detail subbands to capture the intrinsic geometrical structures that contain both target and clutter information. After directional decomposition, the clutter is eliminated by keeping the diagonal information for target component. Finally, the inverse transform is applied to the remaining subbands for reconstruction of clutter-free GPR image. Results of both simulated and real datasets validate the superiority of MDNF over the state-of-the-art methods, and it improves in the false alarm rate further by 5.5% at maximum detection performance.


Clutter removal Image decomposition Directional filter bank Neighborhood filtering Multiscale transform Ground-penetrating radar 


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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Electronics and Communication Department, Faculty of Electrical and Electronics EngineeringIstanbul Technical UniversityIstanbulTurkey

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