Burst Super-Resolution with Diffusion Models for Improving Perceptual Quality

The core message of this paper is to propose a burst super-resolution method that employs diffusion models to improve the perceptual quality of the super-resolved images, by appropriately conditioning the diffusion model with features extracted from the input burst low-resolution images and starting the reverse process from an intermediate step of the diffusion model.