Joint Photographic Expert Group Recompression

JPEG recompression focuses on further compressing already-compressed JPEG images, leveraging the existing structure to achieve greater efficiency than compressing raw image data. Current research emphasizes developing deep learning-based methods, often employing variational autoencoders or other neural network architectures, to achieve both lossy and lossless recompression. This area is significant because it addresses the vast quantity of existing JPEG data, offering potential for substantial storage savings and improved transmission speeds across various applications, while also highlighting the need for robust models resistant to adversarial attacks.