国防科技大学学报2025，Vol.47Issue(4)：91-110,20.DOI:10.11887/j.issn.1001-2486.24120027
面向图像处理逆问题的扩散模型研究综述
Review of diffusion models for inverse problems in image processing
摘要
Abstract
Diffusion models represent a novel type of generative artificial intelligence models.Compared to traditional networks such as generative adversative networks,variational autoencoders,and flow models,diffusion models are characterized by their robust training,high fidelity and diversity in generation,and strong mathematical interpretability,and so they are widely used in fields of computer vision,signal processing,multi-modal learning and so on.Diffusion models are capable of sufficiently learning and exploring the deep generative priors from the training images,providing a novel paradigm for solving inverse problems in image processing.In order to systematically sort out the development status of diffusion model,especially the latest progress in solving the inverse problem of image processing,the research of diffusion model for the inverse problem of image processing was reviewed.The basic principle and development status of diffusion model was expounded,the main technical route of using diffusion model to solve the inverse problem of image processing and some specific application results in this direction were emphatically introduced,and the future research directions were envisioned.关键词
扩散模型/生成式人工智能/图像处理/逆问题/深度生成先验Key words
diffusion model/generative artificial intelligence/image processing/inverse problem/deep generative prior分类
信息技术与安全科学引用本文复制引用
王泽龙,吴宇航,李健,杨轩..面向图像处理逆问题的扩散模型研究综述[J].国防科技大学学报,2025,47(4):91-110,20.基金项目
国防科技大学自主创新基金资助项目(23-ZZCX-JDZ-01) （23-ZZCX-JDZ-01）
