Histogram Equalization for Grayscale Images and Comparison with OpenCV Library

Tayfun Celebi; Ibraheem Shayea; Ayman A. El-Saleh; Sawsan Ali; Mardeni Roslee

doi:10.1109/MICC53484.2021.9642082

Histogram Equalization for Grayscale Images and Comparison with OpenCV Library

Tayfun Celebi, Ibraheem Shayea, Ayman A. El-Saleh, Sawsan Ali, Mardeni Roslee

Faculty of Electrical and Electronics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

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.

Original language	English
Title of host publication	15th IEEE Malaysia International Conference on Communications
Subtitle of host publication	Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings
Editors	Aznilinda Zainuddin, Nur Idora Abdul Razak
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	92-97
Number of pages	6
ISBN (Electronic)	9781665426763
DOIs	https://doi.org/10.1109/MICC53484.2021.9642082
Publication status	Published - 2021
Event	15th IEEE Malaysia International Conference on Communications, MICC 2021 - Virtual, Online, Malaysia Duration: 1 Dec 2021 → 2 Dec 2021

Publication series

Name	15th IEEE Malaysia International Conference on Communications: Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings

Conference

Conference	15th IEEE Malaysia International Conference on Communications, MICC 2021
Country/Territory	Malaysia
City	Virtual, Online
Period	1/12/21 → 2/12/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE

Keywords

Contrast
Cumulative distribution function
Grayscale histogram equalization
Histogram equalization
Noisy image

Access to Document

10.1109/MICC53484.2021.9642082

Cite this

Celebi, T., Shayea, I., El-Saleh, A. A., Ali, S., & Roslee, M. (2021). Histogram Equalization for Grayscale Images and Comparison with OpenCV Library. In A. Zainuddin, & N. I. A. Razak (Eds.), 15th IEEE Malaysia International Conference on Communications: Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings (pp. 92-97). (15th IEEE Malaysia International Conference on Communications: Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/MICC53484.2021.9642082

Celebi, Tayfun ; Shayea, Ibraheem ; El-Saleh, Ayman A. et al. / Histogram Equalization for Grayscale Images and Comparison with OpenCV Library. 15th IEEE Malaysia International Conference on Communications: Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings. editor / Aznilinda Zainuddin ; Nur Idora Abdul Razak. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 92-97 (15th IEEE Malaysia International Conference on Communications: Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings).

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title = "Histogram Equalization for Grayscale Images and Comparison with OpenCV Library",

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.",

keywords = "Contrast, Cumulative distribution function, Grayscale histogram equalization, Histogram equalization, Noisy image",

author = "Tayfun Celebi and Ibraheem Shayea and El-Saleh, {Ayman A.} and Sawsan Ali and Mardeni Roslee",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 15th IEEE Malaysia International Conference on Communications, MICC 2021 ; Conference date: 01-12-2021 Through 02-12-2021",

year = "2021",

doi = "10.1109/MICC53484.2021.9642082",

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series = "15th IEEE Malaysia International Conference on Communications: Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings",

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Celebi, T, Shayea, I, El-Saleh, AA, Ali, S & Roslee, M 2021, Histogram Equalization for Grayscale Images and Comparison with OpenCV Library. in A Zainuddin & NIA Razak (eds), 15th IEEE Malaysia International Conference on Communications: Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings. 15th IEEE Malaysia International Conference on Communications: Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 92-97, 15th IEEE Malaysia International Conference on Communications, MICC 2021, Virtual, Online, Malaysia, 1/12/21. https://doi.org/10.1109/MICC53484.2021.9642082

Histogram Equalization for Grayscale Images and Comparison with OpenCV Library. / Celebi, Tayfun; Shayea, Ibraheem; El-Saleh, Ayman A. et al.
15th IEEE Malaysia International Conference on Communications: Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings. ed. / Aznilinda Zainuddin; Nur Idora Abdul Razak. Institute of Electrical and Electronics Engineers Inc., 2021. p. 92-97 (15th IEEE Malaysia International Conference on Communications: Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Shayea, Ibraheem

AU - El-Saleh, Ayman A.

AU - Ali, Sawsan

AU - Roslee, Mardeni

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AB - 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.

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Celebi T, Shayea I, El-Saleh AA, Ali S, Roslee M. Histogram Equalization for Grayscale Images and Comparison with OpenCV Library. In Zainuddin A, Razak NIA, editors, 15th IEEE Malaysia International Conference on Communications: Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2021. p. 92-97. (15th IEEE Malaysia International Conference on Communications: Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings). doi: 10.1109/MICC53484.2021.9642082

Histogram Equalization for Grayscale Images and Comparison with OpenCV Library

Abstract

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Bibliographical note

Keywords

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