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All issues Volume 30 / No 5 (October 2025) Wuhan Univ. J. Nat. Sci., 30 5 (2025) 427-440 References
Open Access
Issue
Wuhan Univ. J. Nat. Sci.
Volume 30, Number 5, October 2025
Page(s) 427 - 440
DOI https://doi.org/10.1051/wujns/2025305427
Published online 04 November 2025
  1. Wang Y T, Wang Z Y, Tao D P, et al. AllFocus: Patch-based video out-of-focus blur reconstruction[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2017, 27(9): 1895-1908. [Google Scholar]
  2. Liu Y Q, Du X, Shen H L, et al. Estimating generalized Gaussian blur kernels for out-of-focus image deblurring[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2021, 31(3): 829-843. [Google Scholar]
  3. Tang Z J, Yan S Y, Xu C Q. Adaptive super-resolution image reconstruction based on fractal theory[J]. Displays, 2023, 80: 102544. [Google Scholar]
  4. Gao Y C, Ji H B, Liu W J. Persymmetric adaptive subspace detectors for range-spread targets[J]. Digital Signal Processing, 2019, 89: 116-123. [Google Scholar]
  5. Tikhonov A N, Glasko V B. Use of the regularization method in non-linear problems[J]. USSR Computational Mathematics and Mathematical Physics, 1965, 5(3): 93-107. [Google Scholar]
  6. Mumford D, Shah J. Optimal approximations by piecewise smooth functions and associated variational problems[J]. Communications on Pure and Applied Mathematics, 1989, 42(5): 577-685. [Google Scholar]
  7. Chan T, Esedoglu S, Park F, et al. Total variation image restoration: Overview and recent developments[M]//Handbook of Mathematical Models in Computer Vision. New York: Springer-Verlag, 2005: 17-31. [Google Scholar]
  8. Li W Y, Zhang T, Gao Q L. Non-blind image deblurring via shear total variation norm[J]. Wuhan University Journal of Natural Sciences, 2024, 29(3): 219-227. [Google Scholar]
  9. Ji H, Liu C Q, Shen Z W, et al. Robust video denoising using low rank matrix completion[C]//2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. New York: IEEE, 2010: 1791-1798. [Google Scholar]
  10. Gu S H, Xie Q, Meng D Y, et al. Weighted nuclear norm minimization and its applications to low level vision[J]. International Journal of Computer Vision, 2017, 121(2): 183-208. [CrossRef] [Google Scholar]
  11. Bai M R, Zhang X J, Shao Q Q. Adaptive correction procedure for TVL1 image deblurring under impulse noise[J]. Inverse Problems, 2016, 32(8): 085004. [Google Scholar]
  12. Rahimi Y, Wang C, Dong H B, et al. A scale-invariant approach for sparse signal recovery[J]. SIAM Journal on Scientific Computing, 2019, 41(6): A3649-A3672. [NASA ADS] [CrossRef] [MathSciNet] [Google Scholar]
  13. Xu Z B, Chang X Y, Xu F M, et al. L1/2 regularization: A thresholding representation theory and a fast solver[J]. IEEE Transactions on Neural Networks and Learning Systems, 2012, 23(7): 1013-1027. [CrossRef] [PubMed] [Google Scholar]
  14. Zuo W M, Meng D Y, Zhang L, et al. A generalized iterated shrinkage algorithm for non-convex sparse coding[C]//2013 IEEE International Conference on Computer Vision. New York: IEEE, 2013: 217-224. [Google Scholar]
  15. Jia X X, Feng X C, Wang W W, et al. Bayesian inference for adaptive low rank and sparse matrix estimation[J]. Neurocomputing, 2018, 291: 71-83. [CrossRef] [Google Scholar]
  16. Huo L M, Chen W G, Ge H M, et al. L1-βLq minimization for signal and image recovery[J]. SIAM Journal on Imaging Sciences, 2023, 16(4): 1886-1928. [Google Scholar]
  17. Joshi N, Szeliski R, Kriegman D J. PSF estimation using sharp edge prediction[C]//2008 IEEE Conference on Computer Vision and Pattern Recognition. New York: IEEE, 2008: 1-8. [Google Scholar]
  18. Ono S, Miyata T, Yamada I. Cartoon-texture image decomposition using blockwise low-rank texture characterization[J]. IEEE Transactions on Image Processing, 2014, 23(3): 1128-1142. [NASA ADS] [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
  19. Rudin L I, Osher S, Fatemi E. Nonlinear total variation based noise removal algorithms[J]. Physica D: Nonlinear Phenomena, 1992, 60(1-4): 259-268. [Google Scholar]
  20. Tikhonov A. On the regularization of ill-posed problems[J]. Soviet Mathematics Doklady, 1963, 153(6):1111-1146. [Google Scholar]
  21. Wang Y L, Yang J F, Yin W T, et al. A new alternating minimization algorithm for total variation image reconstruction[J]. SIAM Journal on Imaging Sciences, 2008, 1(3): 248-272. [CrossRef] [MathSciNet] [Google Scholar]
  22. Jiao Y L, Jin Q N, Lu X L, et al. Alternating direction method of multipliers for linear inverse problems[J]. SIAM Journal on Numerical Analysis, 2016, 54(4): 2114-2137. [Google Scholar]

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