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

Elektrik-Elektronik Fakültesi

Istanbul Technical University
A'Sharqiyah University
University of Hail
Multimedia University

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

6 Atıf (Scopus)

Özet

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.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	15th IEEE Malaysia International Conference on Communications
Ana bilgisayar yayını alt yazısı	Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings
Editörler	Aznilinda Zainuddin, Nur Idora Abdul Razak
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
Sayfalar	92-97
Sayfa sayısı	6
ISBN (Elektronik)	9781665426763
DOI'lar	https://doi.org/10.1109/MICC53484.2021.9642082
Yayın durumu	Yayınlandı - 2021
Etkinlik	15th IEEE Malaysia International Conference on Communications, MICC 2021 - Virtual, Online, Malaysia Süre: 1 Ara 2021 → 2 Ara 2021

Yayın serisi

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

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	15th IEEE Malaysia International Conference on Communications, MICC 2021
Ülke/Bölge	Malaysia
Şehir	Virtual, Online
Periyot	1/12/21 → 2/12/21

Bibliyografik not

Publisher Copyright:
© 2021 IEEE

Belgeye Erişim

10.1109/MICC53484.2021.9642082

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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. editör / 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).

@inproceedings{9742616a509644f8bacc26fbd84be6b6,

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",

language = "English",

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

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "92--97",

editor = "Aznilinda Zainuddin and Razak, \{Nur Idora Abdul\}",

booktitle = "15th IEEE Malaysia International Conference on Communications",

address = "United States",

}

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).

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

TY - GEN

T1 - Histogram Equalization for Grayscale Images and Comparison with OpenCV Library

AU - Celebi, Tayfun

AU - Shayea, Ibraheem

AU - El-Saleh, Ayman A.

AU - Ali, Sawsan

AU - Roslee, Mardeni

PY - 2021

Y1 - 2021

N2 - 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.

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.

KW - Contrast

KW - Cumulative distribution function

KW - Grayscale histogram equalization

KW - Histogram equalization

KW - Noisy image

UR - https://www.scopus.com/pages/publications/85123919717

U2 - 10.1109/MICC53484.2021.9642082

DO - 10.1109/MICC53484.2021.9642082

M3 - Conference contribution

AN - SCOPUS:85123919717

T3 - 15th IEEE Malaysia International Conference on Communications: Emerging Technologies in IoT and 5G, MICC 2021 - Proceedings

SP - 92

EP - 97

BT - 15th IEEE Malaysia International Conference on Communications

A2 - Zainuddin, Aznilinda

A2 - Razak, Nur Idora Abdul

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 15th IEEE Malaysia International Conference on Communications, MICC 2021

Y2 - 1 December 2021 through 2 December 2021

ER -

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, editörler, 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

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