Score-based diffusion models for bayesian image reconstruction
2023 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP(2023)
摘要
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. We present experiments on both a linear and a nonlinear reconstruction problem that highlight the strengths and limitations of the approach.
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关键词
image reconstruction,inverse problems in imaging,Bayesian inference,generative modeling,diffusion models
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