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Year 2026 · Volume 3 · Issue 3

Original Article

Revolutionizing Image Colorization with AI: A Deep Learning Approach for Enhanced Accuracy and Efficiency

Nashwan. J. Hussein1 Alyaa Ghazalaha2
1 2 Department of Software, College of Information Technology, University of Babylon, Iraq.

Published Online: September-December 2026

Pages: 01-06

Cite this article

↗ https://www.doi.org/10.59256/indjece.20260303001
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Abstract

It's no secret that colorization is a difficult procedure that calls for an attention to detail. Image processing is a domain that needs this procedure with a reliable solution that can handle large amounts of data. After this complex dilemma, therefore, this survey work explores how machine learning might be applied to address this complex problem by utilizing its ability to produce solutions by analyzing large amounts of relevant data. We put into practice three dependable systems: a Convolutional Neural Network (CNN), a Generative Adversarial Network (GAN), and a Variational Autoencoder (VAE) in order to determine the most efficient DL techniques for colorization. Using the identical colorization tasks, we assessed each system methodically and used the data we collected to determine which approach was the most likely to solve this challenging problem. With this study, we shed light on how DL might transform colorization in image processing and provide an indication of how precise and effective visual content enhancement may become in the future.

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Citations

Nashwan. J. Hussein, Alyaa Ghazalaha, “Revolutionizing Image Colorization with AI: A Deep Learning Approach for Enhanced Accuracy and Efficiency”, Indian Journal of Electronics and Communication Engineering, Volume 03, Issue 03, September-December 2026, PP: 01-06.

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Licensing

© 2026 The Author(s). Published by Fifth Dimension Research Publication.

This is an Open Access article distributed under the terms of 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. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

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