Compressed Image

Compressed image research focuses on efficiently reducing image size while preserving visual quality and enabling downstream tasks like object detection or optical character recognition (OCR). Current efforts concentrate on developing novel deep learning architectures, such as GANs and diffusion models, to improve compression ratios and mitigate artifacts introduced by lossy compression, often incorporating techniques like curriculum pre-training or multi-modal fusion to enhance robustness. This field is crucial for managing the ever-increasing volume of image data generated by various sources, particularly satellite imagery and digital documents, impacting data storage, transmission, and analysis across numerous applications.