

A New Approach to Reduce Guassian Noise in Images using Fuzzy Logic
Abstract
Keywords
References
Kwan B. Y. M., Kwan H. K., Impulse Noise Reduction in Brain Magnetic Resonance Imaging using Fuzzy Filters, World Acad. Sci. Eng. Technol. 2011; 60: 1194–1197p.
Gonzalez R., Wintz P. Digital Image Processing, Addison – Wesley, Boston, MA, USA, 1987.
Fuzzy Logic Tool Box User Guide Matlab (R2009b).
Jayaram B., Fuzzy Inference System based Contrast Enhancement, EUSFLAT-LFA 2011
Hari Krishnanand M., Viswanathan R. A New Concept of Reduction of Gaussian Noise in Images Based on Fuzzy Logic. Appl. Math. Sci. 2013; 7(12): 595–602p.
Sivanandam S.N., Deepa S. N. Principles of Soft Computing. John Wiley & Sons, Inc, 2009.
Mario. I., Chacon. M, Fuzzy Logic for Image Processing, Advanced Fuzzy Logic Techniques in Industrial Applications, 2006.
Andrews H.C., Tescher A.G., Kruger R.P., Image Processing by Digital Computer, IEEE Spectrum, July 1972; 9: 20–32p.
Lee C.S., Kuo V.H., Yu P.T. Weighted Fuzzy Mean Filters for Image Processing, Fuzzy Sets. Syst. 1997; 89: 157–180p.
Kare E., Nachtegael M., Eds., Fuzzy Techniques in Image Processing, New York: Springer– Verlag 2000; 52: Studies in Fuzziness and Soft Computing.
D. Van De. Ville, Nachtegael M., Weken D.V., et al. Noise Reduction by Fuzzy Image Filtering, IEEE T. Fuzzy Syst. August-2003; 11(4): 429–436p.
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