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Low Light Image Enhancement for Dark Images
International Journal of Data Science and Analysis
Volume 6, Issue 4, August 2020, Pages: 99-104
Received: May 10, 2020; Accepted: May 25, 2020; Published: Sep. 7, 2020
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Authors
Akshay Patil, Information Technology, K. K. Wagh Institute of Engineering Education and Research, Nashik, India
Tejas Chaudhari, Information Technology, K. K. Wagh Institute of Engineering Education and Research, Nashik, India
Ketan Deo, Information Technology, K. K. Wagh Institute of Engineering Education and Research, Nashik, India
Kalpesh Sonawane, Information Technology, K. K. Wagh Institute of Engineering Education and Research, Nashik, India
Rupali Bora, Information Technology, K. K. Wagh Institute of Engineering Education and Research, Nashik, India
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Abstract
Image plays an important role in this present technological world and leads to progress in multimedia communication, various research fields related to image processing, etc. Low-light image enhancement specifically addresses images captured in low-light conditions such as nighttime, where the common goal is to brighten and improve the contrast of the image for better visual quality and show details that are hidden in darkness. Research fields that may assist us in lowlight environments, such as object detection, has glossed over this aspect even though breakthroughs-after breakthroughs had been achieved in recent years, most noticeably from the lack of low-light data (less than 2% of the total images) in successful public benchmark datasets such as PASCAL VOC, ImageNet, and Microsoft COCO. To improve image quality, these low-light images are needed to be enhanced. For this purpose, an exclusively dark dataset comprising of images captured in visible light only is proposed. Further, dehazing technique is used for haze removal, histogram equalization (HE) technique is used for contrast enhancement and denoising technique is used for noise removal. Experimental results demonstrate that the proposed method achieves a good performance in low light image enhancement and outperforms state-of-the-art ones in terms of contrast enhancement and noise reduction.
Keywords
Dataset, Dehazing, Denoising, Enhancement, Histogram Equalization, Low-light
To cite this article
Akshay Patil, Tejas Chaudhari, Ketan Deo, Kalpesh Sonawane, Rupali Bora, Low Light Image Enhancement for Dark Images, International Journal of Data Science and Analysis. Vol. 6, No. 4, 2020, pp. 99-104. doi: 10.11648/j.ijdsa.20200604.11
Copyright
Copyright © 2020 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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