한국정보전자통신기술학회논문지 (The Journal of Korea Institute of Information, Electronics, and Communication Technology)

  • 제11권5호
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  • Pages.601-607
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  • 2018
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  • 2005-081X(pISSN)
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  • 2288-9302(eISSN)
한국정보전자통신기술학회 (Korea Information Electronic Communication Technology)
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Efficient Median Filter Using Irregular Shape Window

  • Pok, Gou Chol (Division of Computer and IT Education, Pai Chai University)
  • 투고 : 2018.08.23
  • 심사 : 2018.10.17
  • 발행 : 2018.10.30
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초록

Median filtering is a nonlinear method which is known to be effective in removing impulse noise while preserving local image structure relatively well. However, it could still suffer the smearing phenomena of edges and fine details into neighbors due to undesirable influence from the pixels whose values are far off from the true value of the pixel at hand. This drawback mainly comes from the fact that median filters typically employ a regular shape window for collecting the pixels used in the filtering operation. In this paper, we propose a median filtering method which employs an irregular shape filter window in collecting neighboring pixels around the pixel to be denoised. By employing an irregular shape window, we can achieve good noise suppression while preserving image details. Experimental results have shown that our approach is superior to regular window-based methods.

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참고문헌

  1. J. Tukey, Exploratory Data Analysis. Addison-Wesley Menlo Park, CA, 1977.
  2. T. Huang, G. Yang, and G. Tang, "A fast two-dimensional median filtering algorithm," IEEE Trans. Acoust., Speech, Signal Processing, vol. 27, no. 1, pp. 13-E18, 1979. https://doi.org/10.1109/TASSP.1979.1163188
  3. J. Gil and M. Werman, "Computing 2-D Min, Median, and Max Filters," IEEE Trans. Pattern Anal. Machine Intell., vol. 15, no. 5, pp. 504-507,1993. https://doi.org/10.1109/34.211471
  4. S. Vishaga, S. L. Das, "A survey on switching median filters for impulse noise removal," 2015 Int'l Conf. on Circuit, Power and Comp. Technologies, March 2015.
  5. Lin Yin ; Ruikang Yang ; M. Gabbouj ; Y. Neuvo, "Weighted median filters: a tutorial," IEEE Trans. Circuits Systems II: Analog and Digital Sig. Processing, vol. 43(2), pp. 157-192, 1996. https://doi.org/10.1109/82.486465
  6. T. Chen, K.-K. Ma, L. Chen, "Tri-state median filter for image denoising," IEEE Trans. Image Processing, vol. 8, no. 12, pp. 1834-1838, 1999. https://doi.org/10.1109/83.806630
  7. C. T. Lu, Y. Y. Chen, L.L. Wang, and C.F. Chang, "Removal of salt-and-pepper noise in corrupted image using three-values-weighted approach with variable-size window," Pattern Recognition Letters, vol.80, 188-199, 2016. https://doi.org/10.1016/j.patrec.2016.06.026
  8. S.-J. Ko, Y. H. Lee, "Center weighted median filters and their applications to image enhancement," IEEE Trans. Circuits and Systems, vol. 38, no. 9, pp. 984-993, 1991. https://doi.org/10.1109/31.83870
  9. P. E. Ng, K. K. Ma, "A switching median filter with boundary discriminative noise detection for extremely corrupted images," IEEE Trans. Image Processing, vol.15, no. 6, pp. 1506-1516, 2006. https://doi.org/10.1109/TIP.2005.871129
  10. H.-L. Eng, K.-K. Ma, "Noise adaptive softswitching median filter," IEEE Trans. Image Processing, vol.10, no. 2, pp. 242-251, 2001. https://doi.org/10.1109/83.902289
  11. S. Zhang, M.A. Karim, "A new impulse detector for switching median filters," IEEE Sig. Processing Letters, vol. 9, no. 11, pp. 360-363, 2002. https://doi.org/10.1109/LSP.2002.805310
  12. T. Loupas,W. N. Mcdicken, P. L. Allan, "An adaptive weighted median filter for speckle sup pression in medical ultrasonic images," IEEE Trans. Circuits Systems, vol. 36, no. 1, 1989.
  13. H. Hwang, R. A. Haddad, "Adaptive median filters: new algorithms and results," IEEE Trans. Image Processing, vol. 4, no. 4, pp. 499-502, 1995. https://doi.org/10.1109/83.370679
  14. T. C. Lin, P. T. Yu, "Adaptive two-pass median filter based on support vector machines for image restoration," Neural Computation, vol. 16, no. 2, pp. 332-353, 2004. https://doi.org/10.1162/089976604322742056
  15. A. Roy, J. Singha, S.S. Devi. R.H. Laskar, "Impulse noise removal using SVM classification based fuzzy filter from gray scale images," Signal Processing, vol. 28, 262-273, 2016.
  16. A. Roy, R. H. Laskar, "Non-casual linear prediction based adaptive filter for removal of high density impulse noise from color images," AEU - International Journal of Electronics and Communications vol. 72, 114-124, 2017. https://doi.org/10.1016/j.aeue.2016.12.006
  17. G. Pok, J.-C. Liu, A.S. Nair, "Selective removal of impulse noise based on homogeneity level information," IEEE Trans Image Processing, vol. 12, no. 1, pp. 85-92, 2003. https://doi.org/10.1109/TIP.2002.804278