An Algorithm for Salt and Pepper Noise Removal Based on Information Entropy

Abstract:

By using information entropy to estimate the distribution uniformity of the pixels with a same gray level, an accurate salt and pepper noise detection method is presented based on the statistical property of salt and pepper noise. And then, a new modified mean filter is designed, which sets up noise-centre filtering windows, Moreover, the weighted means are calculated by merely using the non-noise points in each filtering window. The presented filter can efficiently preserve the details of images, avoid the affection of noise points on the restore points, and reduce the dimness of the noise points. Experimental results show that this algorithm has the better performance on noise detection, noise filtering, and the protection of detail.

• Periodical: Applied Mechanics and Materials (Volumes 220-223)
• Pages: 2273-2279
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.220-223.2273
• Online since: November 2012
• Authors: Feng Zhao, Rui Chuan Ma, Jia Qing Ma
• Keywords: Image De-Noising, Information Entropy, Median Filtering, Salt and Pepper Noise

References

[1] A. Bovik: Handbook of Image and Video Processing. (Academic, New York, 2000).

[2] A.I. Kravchonok , B.A. Zalesky and P. V. L. Lukashevich : Pattern Recognition and Image Analysis.Vol.17 (2007), p.402.

[3] S. J. Ko and Y. H. Lee: IEEE transactions on circuits and systems. Vol.38 (1991), p.984.

[4] R. H. Chan, C. Hu and M. Nikolova: IEEE signal process letter. Vol.11 (2004), p.921.

[5] R. H. Chan, C. Hu and M. Nikolova: IEEE transactions on image process. Vol.14 (2005), p.1479.

[6] G. H. Yu, J. H. Huang and Y. Zhou: Applied Mathematics Letters.Vol.23 (2010), p.555.

[7] S. Zhang and M.A. Karim: IEEE signal process letter. Vol.9 (2002), p.360.

[8] S. S. Wang and C. H. Wu: Pattern Recognition, Vol.42(2009), p.2194.

[9] G. Kaliraj and S. Baskar: Image and Vision Computing, Vol.28 (2010), p.458.

[10] J. Wu and C. Tang: Pattern Recognition Letters, Vol.32 (2011), p.1974.

[11] K. S. Srinivasan and D. Ebenezer: IEEE Signal Processing letter, Vol.14 (2007), p.189.

[12] S. S. Chen, X. Yang and G. Gao: Pattern Recognition Letters, Vol.30 (2009), p.460.

[13] W. Luo and S. Antonio: IEEE Transaction on Consumer Electronics.Vol.52 (2006), p.523.

[14] J. F. Cai, R. H. Chan , L. X. Shen and Z. W. Shen: Advances in computational mathematics. Vol.31 (2009), p.87.

[15] T. M. Mitchell: Machine Learning. (McGraw Hill, 1997).

[16] G. H. Wang, D.H. Li and W. M. Pan: Signal Processing, Vol.90 (2010), p.3213.