Date of Publication :25th July 2024

Abstract:A computer-based method for colorizing grayscale images using deep learning techniques. The approach involves converting grayscale images into the LAB color space and employing an encoder decoder architecture within a neural network, specifically utilizing Convolutional Neural Networks. By harnessing the power of deep learning, the model learns the mapping between grayscale and colorized images, enabling effective colorization. The process involves training the model on a dataset of grayscale images paired with their corresponding color versions. The trained model demonstrates the capability to accurately colorize grayscale images, presenting a viable solution for automating the colorization process. The implementation showcases the potential of machine learning in image processing tasks, particularly in enhancing visual content and preserving historical or monochrome imagery.

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