Salt Pepper Noise Reduction Using Euclidean Distance Based Adaptive Filter

Abstract

Nowadays, with the development of technology, there is a possibility of corruption of the image due to some disturbing effects during the image retrieval from the external world. One of these disruptive effects is salt and pepper noise. In this paper, a new filter which called Euclidean Distance Based Adaptive Filter (EDBAF) is proposed to remove salt and pepper noise. In this approach, it is calculated how much the noiseless pixels in the process pixel will affect the center pixel than the center pixel distances. In this way, it has been performed to image enhancement. This approach has been tested on different test images with different image quality parameters. It has been verified that it is better at low and high noise density than other existing filters. 

Keywords

• Görüntü işleme,Görüntü iyileştirme,Gürültü giderme,Uyarlamalı filtre,Tuz ve biber gürültüsü

Öklid Mesafe Tabanlı Uyarlamalı Filtre Kullanılarak Tuz Biber Gürültüsü Giderimi

Abstract

Günümüzde teknolojinin gelişmesiyle dış dünyadan görüntülerin alınması aşamasında bazı bozucu etkilerden dolayı görüntülerin bozulması söz konusudur. Bu bozucu etkilerden biri de tuz ve biber gürültüsüdür. Bu yazıda, tuz ve biber gürültülerinin giderilmesi için Öklid Mesafesi Tabanlı Uyarlamalı Filtre (Euclidean Distance Based Adaptive Filter-EDBAF) isimli yeni bir filtre önerilmektedir. Bu yaklaşımda işlem pencerelerindeki gürültüsüz piksellerin merkez piksele olan mesafelerine göre merkez piksele ne kadar etki edeceği hesaplanmaktadır. Bu sayede imgenin iyileştirilmesi gerçekleştirilmektedir. Bu yaklaşım farklı test imgeleri üzerinde farklı görüntü kalitesi parametreleri üzerinden test edilmiştir. Diğer mevcut filtrelere oranla düşük ve yüksek gürültü yoğunluğunda daha iyi sonuç verdiği doğrulanmıştır.

Keywords

• Görüntü işleme,Görüntü iyileştirme,Gürültü giderme,Uyarlamalı filtre,Tuz ve biber gürültüsü

References

1. [1] T.R. Farshi, “Image noise reduction method based on compatibility with adjacent pixels,” International Journal of Image and Graphics, vol. 3, no. 17, pp. 1750014, 2017.
2. [2] P. Altınışık, E. Ergün, “Özyinelemeli ortanca süzgeç için iki yeni yaklaşım,” 2017 International Artificial Intelligence and Data Processing Symposium, Malatya, Türkiye, 16-17 Eylül, 2017.
3. [3] R.H. Chan, C.W. Ho, M. Nikolova, “Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization,” IEEE Transaction on Image Processing, vol. 10, no. 14, pp. 1479-1485, 2005.
4. [4] K.S. Srinivasan, D. Ebenezer, “A new fast and efficient decision-based algorithm for removal of high density impulse noises,” IEEE Signal Processing Letters, vol. 3, no. 14, pp. 189-192, 2007.
5. [5] A. Dash, S.K. Sathua, “High density noise removal by using cascading algorithms,” 2015 Fifth International Conference on Advanced Computing and Communication Technologies, Haryana, Hindistan, 2015, pp. 96-101.
6. [6] E.S. Chang, C. Hung, W. Liu, W.Yin, “A denoising algorithm for remote sensing images with impulse noise,” Geoscience and Remote Sensing Symposium, Beijing, Çin, 2016, pp. 2905-2908.
7. [7] S. Esakkirajan, T. Veerakumar, A.N. Subramanyam, C.H. PremChand, “Removal of high density salt and pepper noise through modified decision based unsymmetrical trimmed median filter,” IEEE Signal Processing Letters, vol. 5, no. 18, pp. 287-290, 2011.
8. [8] N.K. Chaitanya, P. Sreenivasulu, “Removal of salt and pepper noise using advanced modified decision based unsymmetrical trimmed median filter,” 2014 International Conference on Electronics and Communication System, Coimbatore, Hindistan, pp 13-14, 2014.

9. [9] H. Ibrahim, N.S.P. Kong, T.F. Ng, “Simple Adaptive Median Filter for Removal of Impulse Noise from Highly Corrupted Images,” IEEE Transactions on Consumer Electronics, vol. 4, no. 4, pp 1920–1927, 2008.
10. [10] K.V.R. Teja, N.S. Rao, P.S. Kumar, “Distance based algorithm for removal of salt and pepper noise,” 2017 International Conference on Circuits Power and Computing Technologies, Kollam, Hindistan, pp. 20-21, 2017.
11. [11] P. Karthikeyan, S. Vasuki, “Hybrid approach of efficient decision-based algorithm and fuzzy logic for removal of high density salt and pepper noise in images,” Journal of Circuits, Systems, and Computers, vol. 25, no. 10, 2016.
12. [12] Z. Li, Y. Cheng, K. Tang, Y. Xu, D. Zhang, “A salt and pepper noise filter based on local and global image information” Neurocomputing, vol. 159, pp. 172-185, 2015.
13. [13] E.M. Cherrat, R. Alaoui, H. Bouzahir, W. Jenkal, “High density salt and pepper noise suppression using adaptive dual threshold decision based algorithm in fingerprint images,” 2017 Intelligent Systems and Computer Vision, Fez, Morocco, pp 17-19, 2017.
14. [14] K. Kal, V. Toh, S. Member, N. Ashidi, M. Isa, “Noise adaptive fuzzy switching median filter for salt-and-pepper noise reduction,” IEEE Signal Processing Letters, vol. 3, no. 17, pp. 281-284, 2010.
15. [15] U. Erkan, L. Görkem, “A new method based on pixel density in salt and pepper noise removal,” Turkish Journal of Electrical Engineering and Computer Sciences, vol. 1, no. 26, pp.162-171, 2018.
16. [16] U. Ekran, L. Görkem, S. Enginoğlu, “Different applied median filter in salt and pepper noise,” Computers and Electrical Engineering, vol. 70, pp. 789-798, 2018.