Image processing uses deep learning, like CNNs and GANs, to upscale low-resolution images by predicting missing details. Despite accuracy improvements, high-frequency details are often lacking. Our model uses a GAN framework (generator and discriminator) to produce high-quality, high-resolution images from low-quality inputs.