Real-world defocus deblurring via score-based diffusion models

Real-world defocus deblurring via score-based diffusion models

Abstract Defocus blur commonly arises from the cameras’ depth-of-field limitations. While the deep learning method shows promise for image restoration problems, defocus deblurring requires accurate training data comprising pairs of all-in-focus and defocus images, which can be difficult to collect i...

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Bibliographic Details
Main Authors: Yuhao Li, Haoran Fang, Xiang Lei, Qi Wang, Gang Hu, Jiaqing Dong, Zilong Li, Jiabin Lin, Qiegen Liu, Xianlin Song
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Defocus deblurring
Score-based diffusion model
High-resolution iterative deblurring
Real-world scenarios
Image restoration
Online Access:https://doi.org/10.1038/s41598-025-07326-6
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https://doi.org/10.1038/s41598-025-07326-6

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