Dvadasham (Dodeca) Edge Filter for Impulse Noise, Gaussian Noise, Quantum Noise Reduction in Images
(A Generic Image Filter)
Keywords:
Noise Reduction, Denoising, DEF, Dvadasham, Dodeca, Image Filter, Edge Detection, Fuzzy Filter, Impulse Noise, Gaussian Noise, Quantum NoiseAbstract
All image processing techniques need to extract meaningful information from images. However, the noise generated during image acquisition and transmission degrades the human interpretation, or computer-aided analysis of these images. Therefore, denoising should be performed to improve the image quality for more accurate analysis and diagnosis, So we thought of designing a generic image filter that can be applicable to remove Impulse noise, Gaussian noise, Quantum noise. In this paper we propose a novel image denoising technique Dvadasham (Dodeca) Edge Filter (DEF). We applied this filter on various images, obtained the results by measuring parameters like Standard Deviation, Homogeneity and compared it with the results of existing Fuzzy Filter. The results obtained with DEF are quite promising than Fuzzy Filter.
References
Tinku Acharya and Ajoy K. Ray (2006). Image Processing - Principles and Applications. Wiley InterScience.
Wilhelm Burger and Mark J. Burge (2007). Digital Image Processing: An Algorithmic Approach Using Java. Springer. ISBN 1-84628-379-5 and ISBN 3-540-30940-3Check |isbn= value .
Philips D., “Image Processing in C”, 2nd Edition, ISBN: 0-13- 104548-2 (2000).
R. C. Gonzalez, R. E. Woods, “Digital Image Processing”, Pearson Education, 2001.
B.Chanda, D.Dutta Majumder, “Digital Image Processing and Analysis” Prentice Hall India Publication, 2011.
Muhammad Bilal Ahmad and Tae-Sun Choi, "Local Threshold and Boolean Function Based Edge Detection", IEEE Transactions on Consumer Electronics, Vol. 45, No 3. August 1999.
Barry Truax, ed. (1999). "Handbook for Acoustic Ecology" (Second ed.). Cambridge Street Publishing. Retrieved 2012-08-05.
Harish Kundra , Monika Verma & Aashima, “Filter for Removal of Impulse Noise by Using Fuzzy Logic”, International Journal of Image Processing (IJIP) Volume(3), Issue(5).
Gouchol Pok, Jyh-Charn Liu, and Attoor Sanju Nair, “Selective Removal of Impulse Noise Based on Homogeneity Level Information”, IEEE Transactions On Image Processing, Vol. 12, No. 1, January 2003.
PerrySprawls, Ph.D, http://www.sprawls.org/ppmi2/NOISE/# QUANTUM%20 NOISE for Receptor.
M. Hari Krishnan and R. Viswanathan, “A New Concept of Reduction of Gaussian Noise in Images Based on Fuzzy Logic”, Applied Mathematical Sciences, Vol. 7, 2013, no. 12, 595 – 602.
Dimitri Van De Ville, Member, IEEE, Mike Nachtegael, Dietrich Van der Weken, Etienne E. Kerre, Wilfried Philips, Member, IEEE, and Ignace Lemahieu, Senior Member, IEEE. “Noise Reduction by Fuzzy Image Filtering”, IEEE Transactions On Fuzzy Systems, Vol. 11, No. 4, August2003.
Gauss, Carl Friedrich (1816). "Bestimmung der Genauigkeit der Beobachtungen". Zeitschrift für Astronomie und verwandt Wissenschaften 1: 187–197.
Walker, Helen (1931). Studies in the History of the Statistical Method. Baltimore, MD: Williams & Wilkins Co. pp. 24–25.
K. Arakawa, “Median filter based on fuzzy rules and its application to image restoration,” Fuzzy Sets Syst., pp. 3–13, 1996.
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