An Efficient Directional Weighted Median Switching Filter for Impulse Noise Removal in Medical Images

  • Madhu S. Nair
  • J. Reji
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 192)


This paper proposes a new efficient directional weighted median filter for impulse noise removal in medical images. The proposed method consists of two phases: noise detection and noise filtering. In this method, detection is done by Directional Weighted Median (DWM) detection [1], and filtering is applied to only corrupted pixels in the noisy image. The noise detection stage is based on the differences between the current pixel and its neighbours aligned in the main four directions in the considered window. The weighted median filter is then applied on directional pixel values as well as on uncorrupted pixels in the selected window by giving appropriate weights for the better restoration of corrupted medical images. Extensive experimental analysis shows that the proposed technique can be used for medical images with different impulse type noises. Both quantitative and qualitative analysis shows the superiority of the proposed method over other filters.


Directional Weighted Median (DWM) Efficient directional weighted median filter Medical image denoising Noise Models Impulse noise Salt and pepper noise 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Dong, Y., Xu, S.: A New Directional Weighted Median Filter for Removal of Random-Valued Impulse Noise. IEEE Signal Process Lett. 14(3), 193–196Google Scholar
  2. 2.
    Toprak, A., Güler, I.: Impulse noise reduction in medical images with the use of switch mode fuzzy adaptive median filter. Digital Signal Processing 17, 711–723 (2007)CrossRefGoogle Scholar
  3. 3.
    Pratt, W.K.: Digital Image Processing. John Wiley & Sons, Chichester (1978)zbMATHGoogle Scholar
  4. 4.
    Abreu, E., Lightstone, M., Mitra, S.K., Arakawa, K.: A new efficient approach for the removal of impulse noise from highly corrupted images. IEEE Trans. Image Process. 5, 1012–1025 (1992)CrossRefGoogle Scholar
  5. 5.
    Eng, H.-L., Ma, K.-K.: Noise adaptive soft-switching median filter. IEEE Trans. Image Process. 10(2), 242–251 (2001)CrossRefzbMATHGoogle Scholar
  6. 6.
    Zhang, S., Karim, M.A.: A new impulse detector for switching median filters. IEEE Signal Processing Letters 9(4), 360–363 (2002)CrossRefGoogle Scholar
  7. 7.
    Wang, Z., Zhang, D.: Progressive switching median filter for the removal of impulse noise from highly corrupted images. IEEE Transactions on Circuits System II 46(1), 78–80 (1999)CrossRefGoogle Scholar
  8. 8.
    Nair, M.S., Raju, G.: A new fuzzy-based decision algorithm for high-density impulse noise removal. Signal Image and Video Processing, doi:10.1007/s11760-010-0186-4Google Scholar
  9. 9.
    Hussain, A., Arfan Jaffar, M., Mirza, A.M.: A hybrid image restoration approach: fuzzy logic and directional weighted median based uniform impulse noise removal. Springer-Verlag London Limited, Heidelberg (2009)Google Scholar
  10. 10.
    Wang, Z., Bovik, A.C.: A universal image quality index. IEEE Signal Process. Lett. 9(3), 81–84 (2002)CrossRefGoogle Scholar
  11. 11.
    Nair, M.S., Revathy, K., Tatavarti, R.: An Improved Decision-Based Algorithm for Impulse Noise Removal. In: International Congress on Image and Signal Processing - CISP 2008, vol. 1, pp. 426–431. IEEE Computer Society Press, Los Alamitos (2008), doi:10.1109/CISP.2008.21CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Madhu S. Nair
    • 1
  • J. Reji
    • 1
  1. 1.Department of Computer ScienceUniversity of KeralaThiruvananthapuramIndia

Personalised recommendations