CASIA OpenIR
Edge Heuristic GAN for Non-Uniform Blind Deblurring
Zheng, Shuai1,2; Zhu, Zhenfeng1,2; Cheng, Jian3,4; Guo, Yandong5; Zhao, Yao1,2
Source PublicationIEEE SIGNAL PROCESSING LETTERS
ISSN1070-9908
2019-10-01
Volume26Issue:10Pages:1546-1550
Corresponding AuthorZhu, Zhenfeng(zhfzhu@bjtu.edu.cn)
AbstractNon-uniform blur, mainly caused by camera shake and motions of multiple objects, is one of the most common causes of image quality degradation. However, the traditional blind deblurring methods based on blur kernel estimation do not perform well on complicated non-uniform motion blurs. However, recent studies show that GAN-based approaches achieve impressive performance on deblurring tasks. In this letter, to further improve the performance of GAN-based methods on deblurring tasks, we propose an edge heuristic multi-scale generative adversarial network (GAN), which uses the coarse-to-fine scheme to restore clear images in an end-to-end manner. In particular, an edge-generated network is designed to generate sharp edges as auxiliary information to guide the deblurring process. Furthermore, We propose a hierarchical content loss function for deblurring tasks. Extensive experiments on different datasets show that our method achieves state of the art performance in dynamic scene deblurring.
KeywordBlind image deblurring generative adversarial network edge heuristic
DOI10.1109/LSP.2019.2939752
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61572068] ; National Natural Science Foundation of China[61532005] ; Fundamental Research Funds for the Central Universities of China[2019YJS048] ; Fundamental Research Funds for the Central Universities of China[2019JBM018]
Funding OrganizationNational Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities of China
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000487071700001
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/27011
Collection中国科学院自动化研究所
Corresponding AuthorZhu, Zhenfeng
Affiliation1.Beijing Jiaotong Univ, Inst Informat Sci, Beijing 100044, Peoples R China
2.Beijing Key Lab Adv Informat Sci & Network Techno, Beijing 100044, Peoples R China
3.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
4.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
5.Xpeng Motors, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Zheng, Shuai,Zhu, Zhenfeng,Cheng, Jian,et al. Edge Heuristic GAN for Non-Uniform Blind Deblurring[J]. IEEE SIGNAL PROCESSING LETTERS,2019,26(10):1546-1550.
APA Zheng, Shuai,Zhu, Zhenfeng,Cheng, Jian,Guo, Yandong,&Zhao, Yao.(2019).Edge Heuristic GAN for Non-Uniform Blind Deblurring.IEEE SIGNAL PROCESSING LETTERS,26(10),1546-1550.
MLA Zheng, Shuai,et al."Edge Heuristic GAN for Non-Uniform Blind Deblurring".IEEE SIGNAL PROCESSING LETTERS 26.10(2019):1546-1550.
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