Authors:
B. Karthik,T.Krishnakumar,M.Sundararajan,M.Sriram,DOI NO:
https://doi.org/10.26782/jmcms.spl.2019.08.00041Keywords:
Noise Elimination,MCF,IEF,PSNR,Abstract
Video are degraded through Impulse Noise (salt and pepper noise- SPN). This methodology that produces the noisy to noise free video frames. Median filters are recognized for their ability to eliminate impulse noise and protects original type. This system is to differentiate between noisy pixels and therefore the noisy free pixels. We have projected an algorithm known as modified Cascaded filter (MCF) algorithm for the restoration of color or gray scale video frames which could be significantly degraded by using salt and pepper noise. This planned algorithmic rule indicates higher results than few best algorithms. To verify the algorithmic rule with varied color video frames and it offers higher outcome with high IEF and PSNR.Refference:
I. AstolaJ.andP.Kuosmanen, Fundamentals of Non-Linear Digital Filtering,
BocRaton, CRC, 1997.
II. Cyriac, Marykutty; Karthik, B; , Detection of Optical Disc and Exudates in
Colour Fundus Images, Indian Journal of Science and Technology, V-8, I-32, pp-
, 2015.
III. KarthikB, TVUK Kumar, MA Dorairangaswamy, E Logashanmugam, “Removal
of High Density Salt and Pepper Noise Through Modified Cascaded Filter”,
Middle East Journal of Scientific Research, 20(10),pp 1222-1228, 2014.
IV. KarthikB, TVUK Kumar, “Noise Removal Using Mixtures of Projected Gaussian
Scale Mixtures”, World Applied Sciences Journal, 29(8), pp 1039-1045, 2014.
V. Kumar, TVU Kiran; Karthik, B; Kumaran, E Bharath; , Visual Secret Sharing
Scheme for JPEG Compressed Images, Middle-East Journal of Scientific
Research, V-12, I-12, pp-1873-1880, 2012.
VI. Karthik, B; Kirankumar, TVU; Raj, M Sundar; BharathKumaran, E; , Simulation
and Implementation of Speech Compression Algorithm in VLSI, Middle-East
Journal of Scientific Research, V-20, I-9, pp-1091-1092, 2013.
VII. Pitas I. and A.N.Venetsanopoulous, Non-linear Digital Filter Principles and
Applications, (Boston: Kluwer Academic publishers, 1990).
VIII. PrattW.K., Digital Image Processing (New York: Wiley 1978).
IX. RemziOten and Rui J. P. de Figueiredo, “Adaptive alpha-trimmed mean filters
under deviations from assumed noise model,” IEEE Tran.on Image Processing,
vol. 13, no. 5, pp. 627-639, 2004
X. Srinivasan E.andD.Ebenezer, “A New Class of Midpoint Type Non-linear Filters
for Eliminating Short and Long Tailed Noise in Images, Third International
Symposium on Wireless Personal Multimedia Communication, November 2000,
Bangkok, Thailand.
XI. VeerakumarT., S. Esakkirajan, IlaVennila, “Combined Fuzzy Logic and
Unsymmetric Trimmed Median Filter Approach for the Removal of High
Density Impulse Noise”, WSEAS Transactions on Signal Processing, Issue 1,
Volume 8, January 2012.
XII. Yi Hong, Sam Kwong, Hanli Wang, “Decision-Based Median Filter Using KNearest
Noise-Free Pixels” IEEE ICASSP 2009