An approach for High Density Impulse Noise Removal using Modified Median Filter

Sudha Tak, Prof. Sandeep Gangane

Abstract


Images are imitations of real world objects. Often an image is a two dimensional (2D) signal f(x,y) represent the amplitude or intensity of the image. In the Transmission of images, they are corrupted by salt and pepper noise, due to faulty communications. Salt and Pepper noise is also known as Impulse noise. The intention of filtering is to eradicate the impulses so that the noise less image is fully enhanced with slightest signal distortion. The best-known and most commonly used nonlinear digital filters, based on order statistics are median filters, also known as Simple Median Filter (SMF). Median filters are recognized for their capability to remove impulse noise without damaging the edges. The main aim of this work is to modify the existing median filters and implement the modified median filter for reduction of high density impulse noise (salt & pepper noise). Then evaluate the performance of the algorithm using MSE & PSNR parameters.


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References


Priyanka Punhani and Dr. Naresh, "Noise Removal In MR Images Using Non Linear Filters", 6th ICCCNT - 2016 July 13 - 15, 2016.

Tian Bai and Jieqing Tan, "Automatic Detection and Removal of High Density Impulse Noises", IET Image Process, Vol. 09, Issue 02, pp. 162-172, 2015.

Dash, Arabinda, and Sujaya Kumar Sathua. "High Density Noise Removal by Using Cascading Algorithms" in Advanced Computing & Communication Technologies (ACCT), 2015 Fifth International Conference on, pp. 96- 101. IEEE, 2015.

Chauhan, Arjun Singh, and Vineet Sahula. "High Density Impulsive Noise Removal Using Decision Based Iterated Conditional Modes" in Signal Processing, Computing and Control (ISPCC), 2015 International Conference on, pp. 24- 29. IEEE, 2015.

Utaminingrum, Fitri, Keiichi Uchimura, and Gou Koutaki. "High Density Impulse Noise Removal Based On Linear Mean Median Filter" in Frontiers of Computer Vision,(FCV), 2013 19th Korea-Japan Joint Workshop on, pp. 11-17. IEEE, 2013.

S. M. Mahbubur Rahman, M. Omair Ahmad, M. N. S. Swamy, "Wavelet-Domain Image De-Noising Algorithm Using Series Expansion Of Coefficient P.D.F. In Terms Of Hermite Polynomials", 2005.

D. Gleich, P. Planinsic, and Z. Cucej, "Low Bitrate Video Coding Using Wavelet Transform", In Proc. of the EURASIP conference on Video/Image Processing and Multimedia Communications, pages 369 – 374, 2003.

D. Marpe and H. L. Cycon, "Very Low Bit Rate Video Coding Using Wavelet-Based Techniques", IEEE Transactions on Circuits and Systems for Video Technology, 9:85 – 94, 1999.

A. Said and W. A. Pearlman. "A New, Fast, And Efficient Image Codec Based On Set Partitioning In Hierarchical Trees". IEEE Transactions on Circuits and System for Video Techniques, 6:243– 250, 1996.

Hwang, Humor, and Richard A. Haddad. "Adaptive median filters: new algorithms and results" in Image Processing, IEEE Transactions


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