Brain MR Image Enhancement using Average Intensity Replacement Based on GWOHE Algorithm
Vidyasaraswathi H. N.1, Hanumantharaju M. C.2
1Vidyasaraswathi H. N.*, Department of ECE, Bangalore Institute of Technology, Bangalore, India.
2Hanumantharaju M. C., Department of ECE, BMS Institute of Technology and Management, Bangalore, India.
Manuscript received on January 26, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 3193-3199 | Volume-9 Issue-3, February 2020. | Retrieval Number: C6072029320/2020©BEIESP | DOI: 10.35940/ijeat.C6072.029320
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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: The most important task in MR Image Enhancement is to obtain a high resolution optimized visual image using advanced image processing techniques. Most of the life photographs and various images such as aerial, medical and satellite are associated with noise and low grade intensity. To improve the quality for better visual appearance, noise has to be suppressed and contrast has to be enhanced. Traditional contrast improvement techniques do best for various images. But for MRI of brain images, there are chances of misrecognization of WMH (White Matter Hyperintensities) as Cerebrospinal fluid (CSF) in traditional enhancement techniques. To overcome this ambiguity and enhance WMH regions of MRI brain images, a novel algorithm has been proposed in this paper. This algorithm is called as Mean Intensity replacement based on Grey Wolf Optimization Histogram Equalization (GWOHE). This technique is applied on FLAIR images and comparison is tabulated along with existing technique for parameters such as PSNR, AMBE.
Keywords: Image Enhancement, FLAIR Images, PSNR, Average Gradient.