Image Restoration by Denoising Diffusion Models with Iteratively Preconditioned Guidance

arXiv:2312.16519v2 Announce Type: replace-cross
Abstract: Training deep neural networks has become a common approach for addressing image restoration problems. An alternative for training a "task-specific" network for each observation model is to use pretrained deep denoisers for imposing only the signal's prior within iterative algorithms, without additional training. Recently, a sampling-based variant of this approach has become popular with the rise of diffusion/score-based generative models. Using denoisers for general purpose restoration requires guiding the iterations to ensure agreement of the …

abstract algorithms arxiv become cs.cv denoising diffusion diffusion models eess.iv guidance image image restoration iterative network networks neural networks observation prior signal training type