[1] S.Q. Yuan, Y.H. Tan, “Impulse noise removal by a global–local noise detector and adaptive median filter”, Signal Processing, vol. 86, no.8, pp. 2123-2128, 2006.
[2] P.-E. Ng, K.-K. Ma, “A switching median filter with boundary discriminative noise detection for extremely corrupted image”, IEEE Transactions on Image Processing, vol. 15, no. 6, pp. 1506-1516, 2006.
[3] Z.F. Deng, Z.P. Yin, Y.L. Xiong, “High probability impulse noise- removing algorithm based on mathematical morphology”, IEEE Signal Processing Letters, vol. 14, no. 1, pp. 31-34, 2007.
[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. 14, no. 3, pp. 189-192, 2007.
[5] P.Y. Chen, C.Y. Lien, “An efficient edge-preserving algorithm for removal of salt-and-pepper noise”, IEEE Signal Processing Letters, vol. 15, pp. 833-836, 2008.
[6] X.M. Zhang, Y.L. Xiong, “Impulse noise removal using directional weighted noise detector and adaptive weighted mean filter”, IEEE Signal Processing Letters, vol. 16, no. 4, pp. 295-298, 2009.
[7] S.S. Wang, C.H. Wu, “A new impulse detection and filtering method for removal of wide range impulse noises”, Pattern Recognition, vol. 42, no. 9, pp. 2194-2202, 2009.
[8] K.K.V. Toh, N.A.M. Isa, “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] G. Yu, L. Qi, Y. Sun, Y. Zhou, “Impulse noise removal by a non- monotone adaptive gradient method”, Signal Processing, vol. 90, no. 10, pp. 2891-2897, 2010.
[10] X. Zhang, Y. Zhan, M. Ding, W. Hou, Z. Yin, “Decision-based non-local means filter for removing impulse noise from digital images”, Signal Processing, vol. 93, pp. 517-524, 2013.
[11] S. Esakkirajan, T. Veerakumar, A. N. Subramanyam, C. H. PremChand, “Removal of High Density Salt and Pepper Noise Through Modified Decision Based Unsymmetric Trimmed Median Filter,” IEEE Signal Process Letters., vol. 18, no. 5, pp. 287-290, 2011.
[12] G.Yu, S. Niu and J. Ma, “A hybrid spectral gradient method for removing salt-and-pepper impulse noise,” Image and Signal Processing (CISP), vol. 2, pp. 765-768, 2011.
[13] P. Shanmugavadivu and P. S. Eliahim Jeevaraj, “Fixed-Value Impulse Noise Suppression for Images using PDE based Adaptive Two-Stage Median Filter,” ICCCET, pp. 290 - 295, 2011.
[14] R. C. Gonzalez and R. E. Wood, Digital Image Processing. Prentice Hall, 2002.
[15] Z. Wang, A.C. Bovik, H.R. Sheik, E.P. Simoncelli, “Image quality assessment: from error visibility to structural similarity”, IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 1-14, 2004.
[16] 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.
[17] T. Chen, K. K. Ma, and L. H. Chen, “Tri-state median filter for image denoising,” IEEE Trans. Image Process., vol. 8, no. 12, pp. 1834-1838, Dec. 1999.
[18] R. C. Hardie and C. G. Boncelet, “LUM filters: A class of rank-order-based filters for smoothing and sharpening,” IEEE Trans. Signal Process., vol. 41, no. 3, pp. 1834-1838, Mar. 1993.
[19] H. K. Kwan, “Fuzzy filters for noise reduction in images,” in Fuzzy Filters for Image Processing, 1st ed, M. Nachtegael, D. Van der Weken, D. Van De, and E. E. Kerre, Eds. Heidelberg, Germany: Physica Verlag, vol. 122, pp. 25-53, 2003.
[20] K. and G. Tolt, “Real-time image noise cancellation based on fuzzy similarity,” in Fuzzy Filters for Image Processing, 1st ed, M. Nachtegael, D. Van der Weken, D. Van De Ville, and E. E. Kerre, Eds. Heidelberg, Germany: Physica Verlag, vol. 122, pp. 54-71, 2003.
[21] J. H.Wang and H. C. Chiu, “An adaptive fuzzy filter for restoring highly corrupted images by histogram estimation,” Proc. Nat. Sci. Council, A, vol. 23, pp. 630-643, 1999.
[22] C. S. Lee, Y. H. Kuo, and P. T. Yu, “Weighted fuzzy mean filters for image processing,” Fuzzy Sets Syst., vol. 89, pp. 157-180, 1997.
[23] F. Farbiz, M. B. Menhaj, and S. A. Motamedi, “Edge preserving image filtering based on fuzzy logic,” in Proc. 6th EUFIT Conf., pp. 1417-1421, 1998.
[24] F. Farbiz and M. B. Menhaj, “A fuzzy logic control based approach for image filtering,” in Fuzzy Techniques in Image Processing, 1st ed, E. E. Kerre and M. Nachtegael, Heidelberg, Germany: Physica Verlag, vol. 52, pp. 194-221, 2000.
[25] F. Russo and G. Ramponi, “A fuzzy filter for images corrupted by impulse noise,” IEEE Signal Process. Lett., vol. 3, no. 6, pp. 168-170, 1996.
[26] K. Arakawa, “Median filter based on fuzzy rules and its application to image restoration,” Fuzzy Sets Syst., vol. 77, pp. 3-13, 1996.
[27] F. Russo, “Removal of impulse noise using a FIRE filter,” in Proc. 3rd IEEE Int. Conf. Image Processing, pp. 975-978, 1996.
[28] F. Russo, “Fire operators for image processing,” Fuzzy Sets Syst., vol. 103, pp. 265-275, Apr. 1999.
[29] S. Schulte et al, “A Fuzzy Impulse Noise Detection and Reduction Method,” IEEE Transactions on Image Processing, vol. 15, no. 5, 2006.
[30] S. Sadeghia, “An efficient method for impulse noise reduction from images using fuzzy cellular automata,” Int. J. Electron. Commun., vol. 66, pp. 772-779, 2012.
[31] S. Liang,” A Novel Two-Stage Impulse Noise Removal Technique Based on Neural Networks and Fuzzy Decision,” International Journal of Computer Applications, vol. 16, no. 4, pp. 863-873, 2008.
[32] U. Sahin, S. Uguz and F. Sahin, “Salt and pepper noise filtering with fuzzy-cellular automata”, Computers and Electrical Engineering, vol. 40, pp. 59-69, 2014.
[33] C. Budak, M. Tu¨rk, A. Toprak, “Reduction in impulse noise in digital images through a new adaptive artificial neural network model”, Neural Comput & Applic, vol. 26, pp.835-843, 2015.