PEWARNAAN CITRA GRAYSCALE MENGGUNAKAN GENERATIVE ADVERSARIAL NETWORKS (GANs)

ZHAFRAN, MUHAMMAD and Rachmatullah, M. Naufal and Fachrurrozi, Muhammad (2025) PEWARNAAN CITRA GRAYSCALE MENGGUNAKAN GENERATIVE ADVERSARIAL NETWORKS (GANs). Undergraduate thesis, Sriwijaya University.

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Abstract

Automatic grayscale image colorization is a challenge in computer vision that aims to transform black-and-white images into realistic color images. This study develops a colorization model based on generative adversarial networks using the Pix2Pix architecture, with U-Net as the generator and PatchGAN as the discriminator. Training was conducted in the CIELAB color space with three different learning rate configurations. The best results were obtained in configuration 3 (learning rate 0.000001) with an SSIM of 0.8909 and an MAE of 0.0762. Analysis shows that green and blue colors increasingly resemble the ground truth, while red still exhibits slight intensity deviations. The model effectively colorizes distinct objects but struggles with colors of high contrast.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	pewarnaan citra, generative adversarial networks, Pix2Pix, deep learning, computer vision.
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Muhammad Zhafran
Date Deposited:	20 Mar 2025 02:02
Last Modified:	20 Mar 2025 02:02
URI:	http://repository.unsri.ac.id/id/eprint/169388

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