Dynamic-Clustering Extreme Intensity Prior Based Blind Image Deblurring-Reference-Cited by-同舟云学术

Dynamic-Clustering Extreme Intensity Prior Based Blind Image Deblurring

Published:2023-09-12 Issue:1 Volume:66 Page:22-36
ISSN:0924-9907
Container-title:Journal of Mathematical Imaging and Vision
language:en
Short-container-title:J Math Imaging Vis

Author:

Li Xiaopan,Wu Shiqian,Xie Shoulie,Agaian Sos

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Geometry and Topology,Computer Vision and Pattern Recognition,Condensed Matter Physics,Modeling and Simulation,Statistics and Probability

Link

https://link.springer.com/content/pdf/10.1007/s10851-023-01161-y.pdf

Reference41 articles.

1. Chang, C.-F., Wu, J.-L., Chen, K.-J.: A hybrid motion deblurring strategy using patch based edge restoration and bilateral filter. J. Math. Imaging Vis. 60(7), 1081–1094 (2018)

2. Chen, L., Fang, F., Wang, T., Zhang, G.: Blind image deblurring with local maximum gradient prior. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1742–1750 (2019)

3. Hsieh, P.-W., Shao, P.-C.: Blind image deblurring based on the sparsity of patch minimum information. Pattern Recogn. 109, 107597–107613 (2021)

4. Yu, X., Xie, W.: Single image blind deblurring based on salient edge-structures and elastic-net regularization. J. Math. Imaging Vis. 62(8), 1049–1061 (2020)

5. Ren, D., Zhang, K., Wang, Q., Hu, Q., Zuo, W.: Neural blind deconvolution using deep priors. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3341–3350 (2020)

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