Image Restoration Technique with Non Linear Filters
International Journal of Engineering Trends and Technology (IJETT) | |
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© 2011 by IJETT Journal | ||
Volume-1 Issue-1 |
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Year of Publication : 2011 | ||
Authors :Charu Khare, Kapil Kumar Nagwanshi | ||
Citation
Charu Khare, Kapil Kumar Nagwanshi. "Image Restoration Technique with Non Linear Filters". International Journal of Engineering Trends and Technology (IJETT),V1(1):1-5 May to June 2011. ISSN:2231-5381. www.ijettjournal.org. Published by Seventh Sense Research Group.
Abstract
In this paper, we presents a novel approach to process the image using different filtering methods by Image Restoration. The aim is to enhance the digital image, reconstruct it into the original form f rom the noisy image. This paper is an overview of effective algorithms that can be used for image restoration. For which, techniques are used on the basis of non linear filters to restore the image. The performance of Histogram Adaptive Fuzzy (HAF) filter is carefully examined and compared with other filters like, Weighted Fuzzy Mean (WFM) filter, Minimum - maximum Detector Based (MDB) filter, Adaptive Fuzzy Mean (AFMF) filter, Centre Weighted Mean (CWM) filter, and Min - max Exclusive Mean(MMEM) filter on the basis of (Peak Signal to Noise Ration) PSNR. Experimental results on images will illustrate the capabilities of all the studied approaches.
References
[1] A.K.Jain, "Fundamentals of Digital Image Processing", Engelwood Cliff, N. J.: Print ice Hall, 2006 .
[2] G. Arce and R. Foster, “Detail - preserving ranked - order based filter for image processing,” IEEE Trans. Acoust., Speech, Signal Processing , vol.37, pp. 83 – 98, 1989.
[3] H. C. Andrews & B. R. Hunt, “Digital Image restoration”, Engl ewood cliffs, NJ, Prentice Hall, 1977.
[4] H.Taub, D.L. Schilling, "Principles of Communication Systems", TMH, 1991 .
[5] I.Pitas and A.N. Vanetsanopoulas. "Non Linear Digital Filters: and Applications", P.Ch. The Kluwer Academic Publishers.
[6] J.Astola And P.Kuosmane n, "Fundamentals Of Nonlinear Digital Filtering", Boca Raton, FL: CRC, 1997.
[7] J.S.Lee,"Digital Image Enhancement and Noise Filtering by use of Local Statistics", IEEE Trans. On Pattern Analysis and. Machine Intelligence, Vol.PAMI - 29, March,1980.
[8] JUNG - HUA WA NG AND HSIEN - CHU CHIU “HAF: an Adaptive Fuzzy Filter for Restoring Highly Corrupted Images by Histogram Estimation” , Vol. 23, No. 5, 1999. pp. 630 - 643 .
[9] Lee, K. C., H. J. Song, and K. H. Sohn (1998) “Detection - estimation based approach for impulsive noise removal.” IEE Electronic Letters , 34(5), 449 - 450.
[10] M. McLoughlin and G. Arce, “Deterministic properties of the recursive separable median filter,” IEEE Trans Acoust., Speech, Signal Processing , vol. ASSP - 35, pp. 98 – 106, 1987.
[11] Nieminen, A., P. Heinonen, and Y. Neuvo (1987) “A new class of detail - preserving filters for image processing” IEEE Trans. Pattern Anal. Mach. Intell ., 9 , 74 - 90
[12] Piotr S. Windyaga, "Fast Implusive Noise Removal", IEEE Trans. On Image Processing, Vol.1 0, No, 1, January 2001.
[13] Qiu, G. (199 6) “An improved recursive median filtering scheme for image processing” IEEE Trans. Image Processing , 5 (4), 646 - 647.
[14] Rafael C. Gonzalez and Richard E. Woods, “Digital image processing”, 2nd edition, Addison - Wesely, 2004 .
[15] Rumelhart, E., G. E. Hinton, and R . J. Williams (1986) Learninginternal representations by error propagation. In: “ Parallel Distributed Processing: Explorations in the Microstructure ofCognition” , 1st Ed., pp. 318 - 362. D.E. Rumelhart and J.L. McClelland Eds. MIT Press, Cambridge, MA, U.S.A .
[16] Satyadhyan Chickerur, Aswatha Kumar, “A Biologically Inspired Filter For Image Restoration”, International Journal of Recent Trends in Engineering, Vol 2, No. 2, November 2009.
[17] S. Haykin, “ Neural Networks” , 2nd ed. Englewood Cliffs, NJ: Prentice - Hall , 1998.
[18] S.J. Kuo and Y.H. Lee, "Center Weighted Median Filters and Their Applications to. Image Enhancement", IEEE Trans. Circuit. Syst.
[19] S. K. Satpathy, S. Panda, K. K. Nagwanshi and C. Ardil, “Image Restoration in Non Linear Filtering Domain using MDB App roch”, International Journal of Signal Processing 6:1 2010.
[20] T.S. Huang, G.J. Yang, And G.Y. Tang, "A Fast Two Dimensional Median Filtering Algorithm", IEEE Trans. On Accustics, Speech, Signal Processing, Vol. ASSP - 27, No.1, Feb 1997.
[21] Takagi, H. and I. Haya shi (1991) “NN - driven fuzzy reasoning”. Int.J.Approximate Reasoning , 5, 191 - 212.
[22] T. Ross, “ Fuzzy Logic With Engineering Applications” . New York: Mc - Graw - Hill, 1995.
[23] T. Y. Young and K. S. Fu, “ Handbook of Pattern Recognition and Image Processing” . New York: Academic, 1997.
[24] W.Y. Han and J. C. Lin, “Minimum – maxmum exclusive mean (MMEM)filter to remove impulse noise from highly corrupted image,” Electron.Lett. , vol. 33, pp. 124 – 125, 1997.
[25] “Image - Restoration”by http://www.owlnet.rice.edu/~elec539/Projects99/BACH/proj2/intro.htm
Keywords
Image processing, Image Restoration, Fuzzy, Impulse Noise, Filters, Histogram Adaptive Fuzzy Filter, Neur al Network.