Spatially adapted parameters selection based on the local constraints for Gaussian plus impulse image deblurring
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11075-024-01924-7.pdf
Reference49 articles.
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2. Hintermüller, M., Rincon-Camacho, M.M.: Expected absolute value estimators for a spatially adapted regularization parameter choice rule in $$L^{1}$$-TV-based image restoration. Inverse Problems 26(8), 085005 (2010)
3. Dong, Y.-Q., Hintermüller, M., Rincon-Camacho, M.M.: Automated regularization parameter selection in multi-scale total variation models for image restoration. J. Math. Imaging. Vis 40(1), 82–104 (2011)
4. Na, H., Kang, M., Jung, M.: An exp model with spatially adaptive regularization parameters for multiplicative noise removal. J. Sci. Comput 75(1), 478–509 (2018)
5. Chen, D.-Q., Cheng, L.-Z.: Spatially adapted total variation model to remove multiplicative noise. IEEE Trans. Image Process 21(4), 1650–1662 (2012)
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