Histogram Equalization for Grayscale Images and Comparison with OpenCV Library

Citation

Celebi, Tayfun and Shayea, Ibraheem and El-Saleh, Ayman A. and Ali, Sawsan and Roslee, Mardeni (2021) Histogram Equalization for Grayscale Images and Comparison with OpenCV Library. In: 2021 IEEE 15th Malaysia International Conference on Communication (MICC), 1-2 Dec. 2021, Malaysia.

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Abstract

The noisy images collected during historical research make it difficult to detail the studies and draw more comprehensive findings. Detailing and updating these images makes it much easier to find information and increases the density of data. Therefore, in this study a histogram equalization method is proposed to reduce the noise in historical images. The method processes the image’s pixel values one by one while also applying the normalization process to keep the density graph steady. In this way, the harmony between density transitions ensures that the quality of the image is higher. The proposed method is compared to the OpenCV algorithm. As a result of this comparison, it is shown that the proposed algorithm is more successful in linearization.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Image segmentation, noisy image, histogram equalization, grayscale histogram equalization, cumulative distribution function, contrast
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 23 Feb 2022 03:58
Last Modified: 23 Feb 2022 03:58
URII: http://shdl.mmu.edu.my/id/eprint/9997

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