JPEG Artifact Correction using Denoising Diffusion Restoration Models. (arXiv:2209.11888v1 [cs.CV])

Diffusion models can be used as learned priors for solving various inverse
problems. However, most existing approaches are restricted to linear inverse
problems, limiting their applicability to more general cases. In this paper, we
build upon Denoising Diffusion Restoration Models (DDRM) and propose a method
for solving some non-linear inverse problems. We leverage the pseudo-inverse
operator used in DDRM and generalize this concept for other measurement
operators, which allows us to use pre-trained unconditional diffusion models
for applications such as …

arxiv denoising diffusion