Open AccessBrain MR Image Enhancement using Average Intensity Replacement Based on GWOHE Algorithm
Author(s) -
H. N. Vidyasaraswathi,
M. C. Hanumantharaju
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.c6072.029320
Subject(s) - artificial intelligence , computer science , fluid attenuated inversion recovery , contrast (vision) , histogram , histogram equalization , image quality , computer vision , pattern recognition (psychology) , contrast enhancement , algorithm , image (mathematics) , magnetic resonance imaging , medicine , radiology
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.