Adaptive Iteration Filter for Suppression of Impulse Noise in Color Images

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Abstract:

New impulse detection and filtering algorithm is proposed in color images. Based on fast peer group filter, the proposed filtering algorithm uses different iteration times to complete filter according to different impulse noise density. The extensive experimental results show that the proposed scheme provides better performance than many of the existing vector filters. Meanwhile, the proposed approach is simple and practical for real-time application.

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116-121

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October 2012

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] J. Astola, et al., Vector median filters, Proc. IEEE, Vol. 78(1990) 678-689.

DOI: 10.1109/5.54807

Google Scholar

[2] P.E. Trahanias, et al., Directional processing of color images: theory and experimental results, IEEE Trans. Image Process, Vol. 5(1996) 868-880.

DOI: 10.1109/83.503905

Google Scholar

[3] JinLiang-hai and LiDe-hua, Improved directional-distance filter, Optics and Precision Engineering, Vol. 15(2007) 798-806.

Google Scholar

[4] R. Lukac, et al., A statistically-switched adaptive vector median filter, Journal of Intelligent and Robotic Systems: Theory and Applications, Vol. 42(2005) 361-391.

DOI: 10.1007/s10846-005-1730-2

Google Scholar

[5] J. Camarena, et al., Fast detection and removal of impulsive noise using peer groups and fuzzy metrics, J. Vis. Commun, Vol. 19(2008) 20-29.

DOI: 10.1016/j.jvcir.2007.04.003

Google Scholar

[6] B. Smolka, Peer group switching filter for impulse noise reduction in color images, Pattern Recognition Lett, Vol. 12(2009) 1016-1025.

DOI: 10.1016/j.patrec.2009.09.012

Google Scholar

[7] S. Morillas, et al., Fuzzy Peer Groups for Reducing Mixed Gaussian-Impulse Noise From Color Images, Ieee T Image Process, Vol. 18(2009).

DOI: 10.1109/tip.2009.2019305

Google Scholar

[8] M. Miloslavski and T.S. Choi, Application of LUM filters with automatic parameter selection to edge detection, Proceedings of the SPIE-The International Society for Optical Engineering, Vol. 3460(1998) 865-871.

DOI: 10.1117/12.323156

Google Scholar

[9] X. Zhang and Y. Xiong, Impulse Noise Removal Using Directional Difference Based Noise Detector and Adaptive Weighted Mean Filter, Ieee Signal Proc Let, Vol. 16(2009) 295-299.

DOI: 10.1109/lsp.2009.2014293

Google Scholar

[10] J. Wu and C. Tang, A new filter for the removal of random-valued impulse noise from highly corrupted images, International Journal of Electronics and Communications(2012).

DOI: 10.1016/j.aeue.2012.03.002

Google Scholar

[11] S. Yuan and Y. Tan, Impulse noise removal by a global–local noise detector and adaptive median filter, Signal Process, Vol. 86(2006) 2123-2128.

DOI: 10.1016/j.sigpro.2006.01.009

Google Scholar

[12] G. Wang, et al., Modified switching median filter for impulse noise removal, Signal Process, 90(2010) 3213-3218.

DOI: 10.1016/j.sigpro.2010.05.026

Google Scholar

[13] L. Jin and D. Li, A switching vector median filter based on the CIELAB color space for color image restoration, Signal Process, Vol. 87(2007) 1345-1354.

DOI: 10.1016/j.sigpro.2006.11.008

Google Scholar

[14] K. Somasundaram and P. Shanmugavadivu, Impulsive noise detection by second-order differential image and noise removal using adaptive nearest neighborhood filter, Int. J. Electron. Commun, Vol. 62(2008) 472-477.

DOI: 10.1016/j.aeue.2007.07.001

Google Scholar

[15] Z. Xu, et al., Geometric Features-Based Filtering for Suppression of Impulse Noise in Color Images, Ieee T Image Process, Vol. 18(2009) 1742-1759.

DOI: 10.1109/tip.2009.2022207

Google Scholar

[16] S. Khodambashi, et al., An Impulse Noise Fading Technique Based On Local Histogram Processing, (2009) 95-100.

Google Scholar

[17] I. Turkmen, Efficient impulse noise detection method with ANFIS for accurate image restoration, Int. J. Electron. Commun. (2011) 132-139.

DOI: 10.1016/j.aeue.2010.02.006

Google Scholar

[18] T. Mélange, et al., A fuzzy filter for the removal of random impulse noise in image sequences, Image Vision Comput(2011) 407-419.

DOI: 10.1016/j.imavis.2011.01.005

Google Scholar

[19] A.M. Eskicioglu and P.S. Fisher, Image quality measures and their performance, Ieee T Commun, Vol. 43(1995) 2959-2965.

DOI: 10.1109/26.477498

Google Scholar