Contrast Enhancement of MRI Images using AHE and CLAHE Techniques
C. Rubini1, N. Pavithra2

1C. Rubini*, Electrical and Electronics Engineering, M.Kumarasamy College of Engineering, Karur, India.
2N.Pavithra,Electronics and Communication Engineering, The Kavery Engineering College, Salem, India.

Manuscript received on November 12, 2019. | Revised Manuscript received on 20 November, 2019. | Manuscript published on December 10, 2019. | PP: 2442-2445 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7017129219/2019©BEIESP | DOI: 10.35940/ijitee.B7017.129219
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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 images require image enhancement, a category of image processing which provides better visualization that make diagnostic more accurate. The most commonly used method for improving the quality of medical image is Contrast enhancement.The main objective is to eliminate the use of contrast dye during the process of MRI scan and to find the parameters MSE, PSNR, AMBE and contrast and compare the result. The histogram equalization (HE) is the widely accepted method which is not productive when the contrast nature differs across the image. Adaptive Histogram Equalization (AHE) overcomes this limitation by considering and developing the mapping for each pixel from the histogram in a neighboring window. Another suitable technique is CLAHE. CLAHE is a refinement of AHE where the enhancement calculation is modified by imposing a user specified level to the height of local histogram. The enhancement is thereby reduced in very uniform areas of the image, which prevents over enhancement of noise and reduces the edge shadowing effect of unlimited AHE. After enhancing the image using AHE and CLAHE the comparison of their parameters is performed. 
Keywords: Contrast Enhancement, Magnetic Resonance Imaging, Histogram Equalization, Adaptive Histogram Equalization, Contrast Limited Adaptive Histogram Equalization, Cumulative Distribution Function, Absolute Mean Brightness Error, Fluid Attenuated Inversion Recovery
Scope of the Article: Properties and Mechanics of Concrete