INFWIDE: Image and Feature Space Wiener Deconvolution Network for Non-Blind Image Deblurring in Low-Light Conditions-Reference-Cited by-同舟云学术

INFWIDE: Image and Feature Space Wiener Deconvolution Network for Non-Blind Image Deblurring in Low-Light Conditions

Published:2023 Issue: Volume:32 Page:1390-1402
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Zhang Zhihong¹^ORCID,Cheng Yuxiao¹,Suo Jinli¹^ORCID,Bian Liheng²^ORCID,Dai Qionghai¹^ORCID

Affiliation:

1. Department of Automation, Institute for Brain and Cognitive Sciences, Tsinghua University, Beijing, China

2. Beijing National Research Center for Information Science and Technology and the Advanced Research Institute of Multidisciplinary Science, Beijing Institute of Technology, Beijing, China

Funder

Ministry of Science and Technology of the People’s Republic of China

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Graphics and Computer-Aided Design,Software

Link

http://xplorestaging.ieee.org/ielx7/83/9991910/10047966.pdf?arnumber=10047966

Reference50 articles.

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4. Single image deblurring with adaptive dictionary learning

5. Fast image deconvolution using hyper-Laplacian priors;krishnan;Advances in neural information processing systems,2009

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