Score-based Diffusion Models for Bayesian Image Reconstruction

Understand

This paper explores the use of score-based diffusion models for Bayesian image reconstruction.

• Diffusion models are an efficient tool for generative modeling.
• Diffusion models can also be used for solving image reconstruction problems.
• We present a simple and flexible algorithm for training a diffusion model and using it for maximum a posteriori reconstruction, minimum mean square error reconstruction, and posterior sampling.