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Filter for Removal of Impulse Noise By Using Fuzzy Logic
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International Journal of Image Processing (IJIP)
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Volume:  3    Issue:  5
Pages:  184-251
Publication Date:   November 2009
ISSN (Online): 1985-2304
195 - 202
Published Date   
CSC Journals, Kuala Lumpur, Malaysia
Keywords   Abstract   References   Cited by   Related Articles   Collaborative Colleague
KEYWORDS:   Digital Image Processing (DIP), Image Enhancement (IE), Fuzzy Logic (FL), Peak-signal-tonoise- ratio (PSNR) 
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Digital image processing is a subset of the electronic domain wherein the image is converted to an array of small integers, called pixels, representing a physical quantity such as scene radiance, stored in a digital memory, and processed by computer or other digital hardware. Fuzzy logic represents a good mathematical framework to deal with uncertainty of information. Fuzzy image processing [4] is the collection of all approaches that understand, represent and process the images, their segments and features as fuzzy sets. The representation and processing depend on the selected fuzzy technique and on the problem to be solved. This paper combines the features of Image Enhancement and fuzzy logic. This research problem deals with Fuzzy inference system (FIS) which help to take the decision about the pixels of the image under consideration. This paper focuses on the removal of the impulse noise with the preservation of edge sharpness and image details along with improving the contrast of the images which is considered as the one of the most difficult tasks in image processing. 
1 Gonzalez, R.C., Woods, R.E., Book on “Digital Image Processing”, 2nd Ed, Prentice-Hall of India Pvt. Ltd.
2 Carl Steven Rapp, “Image Processing and Image Enhancement”, Texas, 1996.
3 R. Vorobel, "Contrast Enhancement of Remotely-Sensed Images," in 6th Int. Conf. Math. Methods in Electromagnetic Theory, Lviv, Ukraine, Sept 1996, pp. 472-475.
4 Tizhoosh, “Fuzzy Image Processing”, © Copyright Springer, 1997.
5 Farzam Farbiz, Mohammad Bager Menhaj, Seyed A. Motamedi, and Martin T. Hagan, “A new Fuzzy Logic Filter for image Enhancement” IEEE Transactions on Systems, Man, And Cybernetics—Part B: Cybernetics, Vol. 30, No. 1, February 2000
6 P. Fridman, "Radio Astronomy Image Enhancement in the Presence of Phase Errors using Genetic Algorithms," in Int. Conf. on Image Process., Thessaloniki, Greece, Oct 2001, pp. 612-615.
Er. Harish Kundra : Colleagues
Er. Monika Verma : Colleagues
Er. Aashima : Colleagues  
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