Removal of High Density Salt & Pepper Noise in Noisy Images Using Decision Based UnSymmetric Trimmed Median Filter (DBUTM)
| International Journal of Computer Trends and Technology (IJCTT) | |
© - Sep to Oct Issue 2011 by IJCTT Journal | ||
Volume-1 Issue-2 | ||
Year of Publication : 2011 | ||
Authors :Dodda Shekar, Rangu Srikanth. |
Dodda Shekar, Rangu Srikanth. "Removal of High Density Salt & Pepper Noise in Noisy Images Using Decision Based UnSymmetric Trimmed Median Filter (DBUTM)"International Journal of Computer Trends and Technology (IJCTT),V2(2):350-357 Sep to Oct Issue 2011 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract: - linear digital filters, based on order statistics are median filters. Median filters are known for their capability to remove impulse noise without damaging the edges. Median filters are known for their capability to remove impulse noise as well as preserve the edges. The effective removal of impulse often leads to images with blurred and distorted features. Ideally, the filtering should be applied only to corrupted pixels while leaving uncorrupted pixels intact. Applying median filter unconditionally across the entire image as practiced in the conventional schemes would inevitably alter the intensities and remove the signal details of uncorrupted pixels. Therefore, a noise-detection process to discriminate between uncorrupted pixels and the corrupted pixels prior to applying nonlinear filtering is highly desirable. Adaptive Median is a “decision-based” or “switching” filter that first identifies possible noisy pixels and then replaces them using the median filter or its variants, while leaving all other pixels unchanged. This filter is good at detecting noise even at a high noise level. The adaptive structure of this filter ensures that most of the impulse noises are detected
References-
[1]. W.K.Pratt, Digital Image Processing (New York: Wiley 1978). [2]. Pitas and A.N. Venetsanopoulous, Non-linear Digital Filter principles and Applications, (Boston: Kluwer Academic publishers, 1990).
[3]. J. Astola and P. Kuosmanen, Fundamentals of Non- Linear Digital Filtering, BocRaton, CRC, 1997
[4]. N.C.Gallagher, Jr. and G.L.Wise, “A Theoretical Analysis of the Properties of Median Filters,” IEEE Trans.Acoust, Speech and Signal, vol.ASSP-29, pp.1136-1141, Dec.1981.
[5]. T.A.Nodes and N.C.Gallagher, “Median Filters: Some Modifications and their properties,” IEEE Trans. Acoust. Speech and Signal Processing, vol. ASSP-30, pp.739-746, April 1987.
[6]. S.Manikandan, O.Uma Maheswari, D.Ebenezer, "An Adaptive Recursive Weighted Median Filter with Improved Performance in Impulsive Noisy Environment", WSEAS Transactions on Electronics, Issue 3, Vol.1, July2004.
[7]. Ho-Ming Lin, "Median Filters with Adaptive Length", IEEE Transactions on Circuits and Systems, Vol.5, No. 6, June 1988
[8]. T.S. Huang, G.J. Yang, and G.Y. Tang, "Fast two dimensional Median Filtering algorithm" , IEEE Transactions on Acoustics, Speech and Signal Processing,1(1995), pp. 499-502.
[9]. Pok, G. Jyh-Charn Liu, "Decision based median filter improved by predictions", ICIP 99(1999) proceedings vol 2 pp 410-413.
[10]. Srinivasan K. S. and Ebenezer D., "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 .
Keywords Median filter, Midpoint filter, trimmed filter, shear sort.