De-noising of MRI Images in Wavelet Domain
Munazza Farha Arshi1, Vandana V. Hanchate2, K. R. Joshi3
1Munazza Farha Arshi*, Student, Department of E&TC, Pune University, India.
2Vandana V. Hanchate, Faculty, Department of E&TC, Pune University, India.
3Dr. K. R. Joshi, Faculty, Department of E&TC, Pune University, India.
Manuscript received on November 15, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on November 30, 2019. | PP: 1947-1949 | Volume-8 Issue-4, November 2019. | Retrieval Number: C6141098319/2019©BEIESP | DOI: 10.35940/ijrte.C6141.118419
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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: Magnetic resonance imaging (MRI) is a diagnostic medical procedure that utilizes solid attractive fields and radio waves to deliver definite pictures of within the body. Extensive research has been completed into whether the attractive fields and radio waves utilized during MRI sweeps could represent a hazard to the human body. No proof has been found to propose there’s a hazard, which means MRI outputs are one of the most secure restorative methodology accessible. MRI has several advantages which make it ideal in numerous situations, in particular, it can identify small changes of structures inside the body. The disadvantage is the noise that degrades the quality of the image. A threestep processing algorithm is proposed to reduce this noise. Here, first it includes soft thresholding in wavelet domain where the original image is divided into blocks that do not overlap. Then it includes restoration of the object boundaries and texture which are lost as a result of the first step and finally enhancing the image using CLAHE (Contrast Limiting Adaptive Histogram Equalization). It is then analyzed using the error parameters like peak signal to noise ratio and mean square error.
Keywords: MRI, Medical Image Denoising, Rician Noise, Soft Thresholding, CLAHE
Scope of the Article: Image Security.