An Efficient Technique to Remove Gaussian Noise and Improve the Quality of Magnetic Resonance Image
N.Rajeswaran1, T.Samraj Lawrence2, R.P.Ramkumar3, N.Thangadurai4
1N.Rajeswaran, Department of EEE, Malla Reddy Engineering College (A), Maisammagauda, Hyderabad, India.
2T.Samraj Lawrence, Department of CSE, Francis Xavier Engineering College (A), Tirunelveli, India.
3P.Ramkumar,, Department of CSE, Malla Reddy Engineering College(A),Maisammaguda,Hyderabad,India.
4N.Thangadurai, School of Engineering and Technology,,Jain University, Bangalore,India
Manuscript received on 02 July 2019 | Revised Manuscript received on 09 July 2019 | Manuscript published on 30 August 2019 | PP: 2375-2377| Volume-8 Issue-10, August 2019 | Retrieval Number: G5224058719/2019©BEIESP | DOI: 10.35940/ijitee.G5224.0881019
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Medical Resonance Imaging (MRI) is very useful in different medical applications for diagnosis the diseases in human body. But the main problem arising in MRI images is presence of various noises. These noises are affecting the originality of the MRI images and producing erroneous results. Here Brain MRI images are used for analysis of noise. Brain images are fractal in nature and especially those images are affected by various noises. In this paper we discussed about the Gaussian noise in brain MRI image. The effect of this noise is reduced by wavelet based thresholding techniques. They are namely Visu shrink, SURE shrink and Bayes shrink. These three methods are applied to the brain MRI images and obtained results are compared by PSNR(Peak signal to Noise ratio), MSE(Mean Square Error),Absolute error, Fractal dimension, IEF(Image Enhancement Factor),Normalized cross correlation and structural content.
Keywords: MRI Images, Gaussian Noise, Wavelet Thresholding, PSNR,MSE, NK, and IEF.
Scope of the Article: Healthcare Informatics