This project implements Single Image Super-Resolution (SISR) specifically for license plate enhancement, inspired by state-of-the-art models like ESRGAN and Residual Dense Networks. It trains a GAN where a generator creates realistic reconstructions and a discriminator evaluates authenticity. The model is trained on the Chinese City Parking Dataset containing diverse license plate images under various conditions.