Authors : A. Amareshwara Sai Nath; Ziaul Haque Choudhury

Volume/Issue : Volume 9 - 2024, Issue 5 - May

Google Scholar : https://tinyurl.com/yasrpp7x

Scribd : https://tinyurl.com/5n8n4jsa

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAY1599

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Deep Image Colonization is a pioneering project aimed to revolutionizing the field of automated image colorization, particularly focusing on enhancing grayscale photographs' visual appeal and historical significance. Leveraging advanced deep learning models like VGG16 and UNET GAN, the project seeks to accurately and faithfully Add images in black and white some color. Through meticulous evaluation and comparison of different colorization algorithms, including real-time display of results and batch processing capabilities, the project strives to provide users with a seamless and intuitive experience. Beyond aesthetic enhancement, the project explores the implications of automated image colorization in various domains, from historical image restoration to creative visual storytelling. By evaluating colorization accuracy and refining models for real-world usage, the project aims to contribute to the advancement of image processing technologies. Ultimately, "Interactive Deep Image Colonization of Quality" endeavour to fill the void left by the past and the present, providing monochromatic imagery through vibrant hues and precision colorization techniques.

Keywords : Automated Image Colorization, Grayscale Photographs, Deep Learning Models, VGG16, UNET GAN.

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