In this paper, we proposed an offline image optimization approach using a deep learning-based compression algorithm. Our method achieves state-of-the-art compression ratios and image quality, outperforming traditional image compression algorithms. The proposed approach has significant potential for applications in image storage, transmission, and retrieval.