An extended sparse model for blind image deblurring
Author:
Funder
PhD research startup foundation of Anhui Jianzhu University
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s11760-023-02888-2.pdf
Reference42 articles.
1. Li, L., Lai, W.-S., Yang, M.-H.: Blind image deblurring via deep discriminative priors. Int. J. Comput. Vis. 127, 1025–1043 (2019). https://doi.org/10.1007/s11263-018-01146-0
2. Pan, J., Sun, D., Pfister, H., Yang, M.-H.: Deblurring images via dark channel prior. IEEE Trans. Pattern Anal. Mach. Intell. 40(10), 2315–2328 (2018). https://doi.org/10.1109/TPAMI.2017.2753804
3. Ren, W., Cao, X., Pan, J., Guo, X., Zuo, W., Yang, M.-H.: Image deblurring via enhanced low-rank prior. IEEE Trans. Image Process. 25(7), 3426–3437 (2016). https://doi.org/10.1109/TIP.2016.2571062
4. Xu, L., Jia, J.: Two-phase kernel estimation for robust motion deblurring. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) Computer Vision - ECCV 2010, pp. 157–170. Springer, Berlin, Heidelberg (2010)
5. Dong, J., Pan, J., Sun, D., Su, Z., Yang, M.-H.: Learning data terms for non-blind deblurring. In: Computer Vision – ECCV 2018, pp. 777–792. Springer, Cham (2018)
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