Absolute Difference Based Progressive Switching Median Filter for Efficient Impulse Noise Removal
 |
International Journal of Engineering Trends and Technology (IJETT) | 
|
| © 2016 by IJETT Journal | ||
| Volume-41 Number-5 |
||
| Year of Publication : 2016 | ||
| Authors : Gophika Thanakumar |
||
| DOI : 10.14445/22315381/IJETT-V41P241 |
Citation
Gophika Thanakumar "Absolute Difference Based Progressive Switching Median Filter for Efficient Impulse Noise Removal", International Journal of Engineering Trends and Technology (IJETT), V41(4),216-222 November 2016. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
Digital images are often corrupted by different noises. These noises can be removed by designing an efficient filter. Based upon the specified operation the pixels are classified. Absolute Difference Based Progressive Switching Median Filter (ADBPSMF) outperforms all other filter for the removal of impulse noise from corrupted images. This filter performs two basic operations for efficient noise removal. The first stage is noise detection and the second is noise filtering. For noise detection, Modified Boundary Discriminative Noise Detection (MBDND) algorithm is used. For noise filtering, Absolute Difference Based Progressive Switching Median Filter (ADBPSMF) is used. The Modified Boundary Discriminative Noise Detection (MBDND) incorporate two modifications after classifying the pixels as follows: (1) Expansion of filtering window. (2) Incorporating spatial and intensity information. By introducing these modifications into the algorithm, it is found that there is increase in the performance and the quality of image has improved. Results are compared with other median filters like Boundary Discriminative Noise Detection Filter (BDND), Tri State Median Filter (TMF), Center Weighted Median Filter (CWMF), Progressive Switching Median Filter (PSMF), Adaptive Threshold Median Filter (ATMF) and it is found that ADBPSMF performs well even at high noise density( 95%).
References
Iyad F. Jafar, Rami A. AlNa’ mneh, and Khalid A. Darabkh,” Efficient Improvement on the BDND Filtering Algorithm for the Removal of High-Density Impulse Noise,” IEEE Trans. Image Process., vol.22, No. 3, MARCH 2013.
[2] T. Veerakumar, S. Esakkirajan, Ila Vennila,“An efficient approach to remove random valued impulse noise in image”, ICRTIT 2012,IEEE 2012.
[3] Kenny Kal Vin Toh, Nor Ashidi Mat Isa,” Cluster- Based Adaptive Fuzzy Switching Median Filter for Universal Impulse Noise Reduction,’’ IEEE Transactions on Consumer Electronics, Vol. 56, No. 4, November 2010.
[4] Tao Chen, Kai-Kuang Ma, and Li-Hui Chen, “Tri-state median filter for image de-noising,” IEEE Trans. Image Process., vol. 8, no. 12, pp. 1834-1838, Dec. 1999.
[5] Yanwei Huang, Binglu Qi and Shaobin Chen,” Modification of advanced boundary discriminative noise detection Algorithm,” IEEE International Conference on Control and Automation (ICCA), June 12-14, IEEE 2013.
[6] Yunfan Wang, Zhu Zhu, Lei Miao, Xiaoguo Zhang, Xueyin Wan,Qing Wang,” A cluster based adaptive switching median filter,” IEEE 2013.
[7] Z. Wang and D.Zhang, “Progressive switching median filter for the removal of impulse noise from highly corrupted images,” IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process., Vol. 46, no. 1,pp. 78-80,Jan. 1999.
[8] Pei-Eng Ng and Kai-Kuang. Ma,” A switching median filter with boundary discriminative noise detection for extremely corrupted images,” IEEE Trans. Image Process.,vol. 15,no. 6, pp. 1506-1516, June.2006.
[9] Wei Ping, LiJunli, Lu Dongming, Chen Gang,” A Fast and Reliable Switching Median Filter for highly corrupted images by Impulse noise,” IEEE 2007,pp . 3427-3430.
[10] Wei Wang and Peizhong Lu,”An efficient switching median filter based on local outlier factor,” IEEE Signal Processing Letters,Vol.18,No.10,October 2011.
[11] S. J. Ko and Y. H. Lee, “Center weighted median filters and their applications to image enhancement,” IEEE Trans. Circuits Syst., vol. 38, no. 9, pp. 984-993, Sep.1991.
[12] D. R. K. Brownrigg, “The weighted median filter,” ACM Commun., vol. 27, no. 8, pp. 807-818, Aug. 1984.
[13] P. S. Windyga, “Fast impulsive noise removal,” IEEE Trans. Image Process., vol. 10, no. 1, pp. 173-179, Jan. 2001.
[14] R. C. Gonzalez and R.E. Woods, Digital Image Processing. Upper Saddle River, NJ: Prentice Hall, 2002.
[15] R. H. Chan, C.-W. Ho, and M. Nikolova, “Salt-and-Pepper Noise Removal by Median-Type Noise Detectors and Detail-Preserving Regularization,” IEEE Trans. Image Process., vol. 14, no. 10, pp.1479–1485, Oct. 2005.
[16] K. S. Srinivasan and D. Ebenezer, “A New Fast and Efficient Decision-Based Algorithm for Removal of High-Density Impulse Noises,” IEEE Signal Process. Lett., vol. 14, no. 3, pp. 189–192, Mar.2007.
Keywords
Absolute Difference Based Progressive Switching Median Filter (ADBPSMF); Adaptive Threshold Median Filter (ATMF) ;Boundary Discriminative Noise Detection Filter (BDND); Center Weighted Median Filter (CWMF; Modified Boundary Discriminative Noise Detection (MBDND); Progressive Switching Median Filter (PSMF); Tri State Median Filter (TMF);