Citation

Sim, Kok Swee and Ee, Chung Seng and Lim, Zheng You (2018) Contrast Enhancement Brain Infarction Images Using Sigmoidal Eliminating Extreme Level Weight Distributed Histogram Equalization. International Journal of Innovative Computing, Information and Control (IJICIC), 14 (3). pp. 1043-1056. ISSN 1349-418X

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Abstract

In modern days, Non-Contrast Computed Tomography (NCCT) is one of the imaging modalities. It performs well in detecting bleeding and tumors in brain images, but less effective in brain infarction diagnosis. Therefore, a contrast enhancement technique known as Sigmoidal Eliminating Extreme Level Weight Distributed Histogram Equalization (SigEELWDHE) is introduced in this paper. It is to improve the contrast of NCCT brain images for better infarction diagnosis. The SigEELWDHE starts to enhance NCCT brain images by sigmoidal filtering function through point processing. Then, the filtered image is then enhanced with Eliminating Extreme Level Weight Distributed Histogram Equalization (EELWDHE) to produce final enhanced image. This method helps to eliminate the maximum and minimum grey level of the image. It modifies histogram of the image using weighting distribution function. 300 NCCT brain images with infarctions are used to evaluate the results of SigEELWDHE through visualization evaluation and Image Quality Assessments (IQA) models. In addition, the performance of the SigEELWDHE is also compared with Brightness preserving Bi-Histogram Equalization (BBHE), Dualistic Sub-Image Histogram Equalization (DSIHE), Recursive Sub-Image Histogram Equalization (RSIHE), Adaptive Gamma Correction with Weighting Distribution (AGCWD), and Extreme-Level-Eliminating Histogram Equalization (ELEHE). The results show that the SigEELWDHE produces better contrast and visualization quality than existing methods.

Item Type:	Article
Uncontrolled Keywords:	Equalizers (Electronics), Contrast enhancement, Histogram weighting distribution, Brain infarction, Histogram equalization, Sigmoidal filtering, Extreme level elimination, Non-contrast computed tomography
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	22 Oct 2020 17:01
Last Modified:	22 Oct 2020 17:01
URII:	http://shdl.mmu.edu.my/id/eprint/7238

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