A color space-based framework for enhancing low-light images using CIELAB transformation

Lee, Kok Xiong and Subaramaniam, Kasthuri and Shah, Umm E Mariya and Shibghatullah, Abdul Samad Bin and Baker, Oras (2025) A color space-based framework for enhancing low-light images using CIELAB transformation. Journal of Robotics, Networking and Artificial Life, 11 (2). pp. 145-151. ISSN 2405-9021 E-ISSN 2352-6386

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Abstract

Image processing dates to the 1960s when it was first applied to improve image quality. With the increased use of digital products in the form of smartphones and cameras, low-light image improvement has come into sharp focus. Several methods have been adopted such as histogram equalization, illumination map estimation, normalizing flows, neural networks, and dark region aware enhancement. This study offers a function for RGB to CIELAB color space transformation and a step-by-step improvement process. Transformation into CIELAB color space offers the feature of separating brightness and color details and improving contrast and image quality. The device independent CIE 1976 (L*, a*, b*) formula that is well adapted to improve images from different sources is employed. An easy-to-use interface has been implemented, enabling users to download low-light photos and restore the improved ones.

Item Type:	Article (Journal)
Uncontrolled Keywords:	CIELAB, image enhancement, neural networks, Tkinter interface
Subjects:	T Technology > T Technology (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Economics and Management Sciences Kulliyyah of Economics and Management Sciences > Department of Finance
Depositing User:	Dr Umm e Mariya Shah
Date Deposited:	21 Dec 2025 23:51
Last Modified:	21 Dec 2025 23:51
Queue Number:	2025-12-Q1295
URI:	http://irep.iium.edu.my/id/eprint/126406

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