Image Colorization Using Deep Learning

Abstract

mage colorization using deep learning is a fascinating field that aims to add color to black and white images automatically. This project explores the use of advanced neural networks, specifically convolutional neural networks (CNNs), to achieve this task efficiently and accurately. By leveraging large datasets of color images paired with their black and white counterparts, the CNN learns to predict plausible colorizations for grayscale input images. The project demonstrates the effectiveness of deep learning techniques in recreating realistic colors while preserving the details of the original images. Through experimentation and evaluation, we showcase the potential of this approach in various applications, including historical photo restoration, artistic expression, and enhancing visual content in multimedia. Overall, this project contributes to the advancement of computer vision and image processing technologies, offering a powerful tool for enriching visual content effortlessly. Keywords: Image Colorization, Deep Learning, Convolutional Neural Networks, Generative