Perception Distortion Trade

Perception distortion trade-off research focuses on optimizing image processing tasks (like super-resolution and compression) to balance high perceptual quality (how realistic an image appears) with low distortion (fidelity to the original). Current research employs generative models, particularly diffusion models and flow models, along with novel optimization techniques like multi-objective optimization and ADMM, to navigate this inherent conflict. This work is significant because it addresses fundamental limitations in achieving both high visual appeal and accurate reconstruction, impacting applications ranging from image compression and transmission to medical imaging and autonomous driving.