INFORMATION CHANGE THE WORLD

International Journal of Mathematical Sciences and Computing(IJMSC)

ISSN: 2310-9025 (Print), ISSN: 2310-9033 (Online)

Published By: MECS Press

IJMSC Vol.1, No.2, Aug. 2015

An Efficient Impulse Noise Removal Image Denoising Technique for MRI Brain Images

Full Text (PDF, 358KB), PP.1-7


Views:66   Downloads:2

Author(s)

Murugan, Balasubramanian

Index Terms

Denoising;Impulse noise;MRI Image;PSNR;SSIM;filters

Abstract

Image enhancement is an important challenge in medical field. There are various techniques for image enhancement during last two decades. The objective of this paper is to remove impulse noise for MRI brain image. This paper proposed an efficient filter for removing impulse noise. The shape of the filter is changed to diamond. Experiments are conducted for various noise levels. The proposed method is compared with the existing Denoising techniques. The experimental results proved that the proposed filter performed well than the other methods.

Cite This Paper

Murugan, Balasubramanian,"An Efficient Impulse Noise Removal Image Denoising Technique for MRI Brain Images", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.1, No.2, pp.1-7, 2015.DOI: 10.5815/ijmsc.2015.02.01

Reference

[1]Pratt William, "Digital Image Processing," John Wiley & Sons, Fourth Edition, 2007.

[2]Gonzalez and Woods, "Digital Image Processing," Pearson Education, Second Edition, 2005. 

[3]H. Hwang and R. A. Hadded, "Adaptive median filter: New algorithms and results," IEEE Trans. Image Process., vol. 4, no. 4, pp. 499 502, Apr. 1995.

[4]P. E. Ng and K. K. Ma, "A switching median filter with boundary discriminative noise detection for extremely corrupted images," IEEE Trans. Image Process., vol. 15, no. 6, pp. 1506–1516, Jun. 2006.

[5]K. S. Srinivasan and D. Ebenezer, "A new fast and efficient decision based algorithm for removal of high density impulse noise," IEEE Signal Processing Letters, vol. 14, no. 3, pp. 189–192, Mar. 2007.

[6]S. Esakkirajan, T. Veerakumar, Adabala N. Subramanyam and C. H. PremChand, "Removal of high density salt and pepper noise throughmodified decision based unsymmetric trimmed median filter," IEEE Signal Processing Letters, vol. 18, no. 5, pp. 287-290, May 2011.

[7]Vivek Chandra, Sagar Deokar, Siddhant Badhe, Rajesh Yawle "Removal of High Density Salt and Pepper Noise Through Modified Decision Based Unsymmetric Trimmed Adaptive Median Filter "International Journal of Engineering and Advanced Technology (IJEAT) ISSN: 2249 – 8958, Volume-2, Issue-3, February 2013.

[8]Buyue Zhang, and Jan p. Allebach, "Adaptive Bilateral Filter for Sharpness Enhancement and Noise Removal"IEEE Transaction on Image Processing , Vol 17.No.5.

[9]Samuel Morillas, Gregori, V., and Sapena, A."Fuzzy peer Groups Reducing Mixed Gaussian-Impulse Noise From Color Images," IEEE Transaction on Image Processing , vol.18.No.7.July 2009.

[10]Chih-Hsing Lin Jia-Shiuan "Switching Bilateral Filter with a Texture/Noise Detector for Universal Noise Removal", IEEE Transaction on Image Processing , Vol 19.No.9, September 2010.[7] Chih-Hsing Lin Jia-Shiuan "Switching Bilateral Filter with a Texture/Noise Detector for Universal Noise Removal", IEEE Transaction on Image Processing , Vol 19.No.9, September 2010.

[11]Iyad F. Jafar, Rami A. "Efficient Improvements on the BDND Filtering Algorithm for the Removal of High-Density Impulse noise", IEEE Transaction on Image Processing , Vol 22.No.3, March 2013.

[12]V. Murugan, T. Avudaiappan, R. Balasubramanian, " A Comparative Analysis of Impulse Noise Removal Techniques on Gray Scale Images", International Journal of Signal Processing, Image Processing and Pattern Recognition Vol.7, No.5 (2014), pp.239-248.

[13]Anuratha.S, Murugan.V, Dr.R.Balasubramanian, "Performance Analysis of Medical Image Denoising Techniques" 11th National Conference on Advanced Image Processing and Networking (NACIPAN'15), 07th March, 2015, National Engineering College, Kovilpatti, Tamilnadu.

[14]PMurugan V , AnuRatha S, Balasubramanian R, "A Hybrid Filtering Technique for MRI Brain Image Denoising" , IJISET - International Journal of Innovative Science, Engineering & Technology, Vol. 2 Issue 5, May 2015.