Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2018, Cilt: 6 , 51 - 55, 01.04.2018
https://doi.org/10.17694/bajece.410249

Öz

Kaynakça

  • [1] Bovik A., Handbook of image and video processing. New York: Academic, 2010.
  • [2] Chan R. H., Ho C. W., Nikolova M., “Salt-and-pepper noise removal by median type noise dedectors and detail-preserving regularization", Vol.14, No.10, pp. 1479-1485, 2005.
  • [3] Nodes T., Gallagher N., "The output distribution of median type filters", IEEE Transactions on Communications, Vol.22, No.5, pp. 532-541, 1984.
  • [4] Hwang H., Haddad R. A., "Adaptive median filters: new algorithms and results", IEEE Transactions on image processing, Vol.4, No.4, pp. 499-502, 1995.
  • [5] Wang Z., Zhang D., "Progressive switching median filter for the removal of impulse noise from highly corrupted images", IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, Vol.46, No.1, pp. 78-80, 1999.
  • [6] Srinivasan K., Ebenezer D., " A new fast and efficient decision-based algorithm for removal of high-density impulse noises", IEEE signal processing letters, Vol.14, No.3, pp. 189-192, 2007.
  • [7] Jayaraj V., Ebenezer D., "A new switching-based median filtering scheme and algorithm for removal of high-density salt and pepper noise in images", EURASIP journal on advances in signal processing, Vol.1, pp. 690218, 2010.
  • [8] Toh K. K. V., Isa N. A. M., "Noise adaptive fuzzy switching median filter for salt-and-pepper noise reduction", IEEE signal processing letters, Vol.17, No.3, pp. 281-284, 2010.
  • [9] Lin T. C., Lin C. M., Liu M. K., Yeh C. T., "Partition-based fuzzy median filter based on adaptive resonance theory", Computer Standards & Interfaces, Vol.36, No.3, pp. 631-640, 2014.
  • [10] Habib M., Hussain A., Rasheed S., Ali M., "Adaptive fuzzy inference system based directional median filter for impulse noise removal", AEU-International Journal of Electronics and Communications, Vol.70, No.5, pp. 689-697, 2016.
  • [11] Katircioglu F., "Segmentation of color images based ‎on relation matrix and edge detection", Master of Science, ‎Dept. Electrical Education, Duzce Universtiy, Duzce, ‎Turkey, 2007.
  • [12] M. Jourlin, J. C. Pinoli, "A model for logarithmic image processing", Journal of microscopy, Vol.149, No.1, pp. 21-35, 1988.
  • [13] Demirci R., "Rule-based automatic segmentation of color images", Int. J. ‎Electronics and Communication(AEÜ), Vol.60, pp. 435-442, 2006.‎
  • [14] Wang Z., Bovik A. C., Sheikh H. R., Simoncelli E. P., "Image quality assessment: from error visibility to structural similarity", IEEE transactions on image processing, Vol.13, No.4, pp. 600-612, 2004.

Noise Adaptive and Similarity Based Switching Median Filter for Salt & Pepper Noise

Yıl 2018, Cilt: 6 , 51 - 55, 01.04.2018
https://doi.org/10.17694/bajece.410249

Öz

Works have been
conducted recently to remove high intensity salt & pepper noise by virtue
of adaptive and switching median filters. One of the cited works is the
Noisy Adaptive Fuzzy Switching Median Filter (NAFSM) by which the noisy pixels
are detected through utilization of image histogram. Noiseless pixels are
left unprocessed while noisy pixels are passed through the noise adaptive
median filter which expands for them. A filter mechanism which performs
decision making in line with local similarity and similarity has been proposed
for NAFSM. Local similarity information in 3x3 mask has been used for
filtering mechanism in the study titled Noise Adaptive and Similar Based
Switching Median Filter (NASBSM). Two thresholds with three regions were
made by virtue of local similarity information. The logic of the approach
was based on more intensive filtering for noisy pixels with high similarity
value with neighboring pixels and less for those with less similarity value
with neighboring pixels. According to the numerical and visual simulation
results of the NASBSM mechanism, it was detected that it eliminates noises with
high density.

Kaynakça

  • [1] Bovik A., Handbook of image and video processing. New York: Academic, 2010.
  • [2] Chan R. H., Ho C. W., Nikolova M., “Salt-and-pepper noise removal by median type noise dedectors and detail-preserving regularization", Vol.14, No.10, pp. 1479-1485, 2005.
  • [3] Nodes T., Gallagher N., "The output distribution of median type filters", IEEE Transactions on Communications, Vol.22, No.5, pp. 532-541, 1984.
  • [4] Hwang H., Haddad R. A., "Adaptive median filters: new algorithms and results", IEEE Transactions on image processing, Vol.4, No.4, pp. 499-502, 1995.
  • [5] Wang Z., Zhang D., "Progressive switching median filter for the removal of impulse noise from highly corrupted images", IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, Vol.46, No.1, pp. 78-80, 1999.
  • [6] Srinivasan K., Ebenezer D., " A new fast and efficient decision-based algorithm for removal of high-density impulse noises", IEEE signal processing letters, Vol.14, No.3, pp. 189-192, 2007.
  • [7] Jayaraj V., Ebenezer D., "A new switching-based median filtering scheme and algorithm for removal of high-density salt and pepper noise in images", EURASIP journal on advances in signal processing, Vol.1, pp. 690218, 2010.
  • [8] Toh K. K. V., Isa N. A. M., "Noise adaptive fuzzy switching median filter for salt-and-pepper noise reduction", IEEE signal processing letters, Vol.17, No.3, pp. 281-284, 2010.
  • [9] Lin T. C., Lin C. M., Liu M. K., Yeh C. T., "Partition-based fuzzy median filter based on adaptive resonance theory", Computer Standards & Interfaces, Vol.36, No.3, pp. 631-640, 2014.
  • [10] Habib M., Hussain A., Rasheed S., Ali M., "Adaptive fuzzy inference system based directional median filter for impulse noise removal", AEU-International Journal of Electronics and Communications, Vol.70, No.5, pp. 689-697, 2016.
  • [11] Katircioglu F., "Segmentation of color images based ‎on relation matrix and edge detection", Master of Science, ‎Dept. Electrical Education, Duzce Universtiy, Duzce, ‎Turkey, 2007.
  • [12] M. Jourlin, J. C. Pinoli, "A model for logarithmic image processing", Journal of microscopy, Vol.149, No.1, pp. 21-35, 1988.
  • [13] Demirci R., "Rule-based automatic segmentation of color images", Int. J. ‎Electronics and Communication(AEÜ), Vol.60, pp. 435-442, 2006.‎
  • [14] Wang Z., Bovik A. C., Sheikh H. R., Simoncelli E. P., "Image quality assessment: from error visibility to structural similarity", IEEE transactions on image processing, Vol.13, No.4, pp. 600-612, 2004.
Toplam 14 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Araştırma Makalesi
Yazarlar

Ferzan Katırcıoglu

Yayımlanma Tarihi 1 Nisan 2018
Yayımlandığı Sayı Yıl 2018 Cilt: 6

Kaynak Göster

APA Katırcıoglu, F. (2018). Noise Adaptive and Similarity Based Switching Median Filter for Salt & Pepper Noise. Balkan Journal of Electrical and Computer Engineering, 6, 51-55. https://doi.org/10.17694/bajece.410249

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