Anisotropic total generalized variation model for Poisson noise removal-Reference-Cited by-同舟云学术

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Anisotropic total generalized variation model for Poisson noise removal

Published:2023-01-14 Issue:13 Volume:82 Page:19607-19620
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Li Daiqin,Liu Xinwu^ORCID

Funder

hunan provincial natural science foundation of china

scientific research fund of hunan provincial education department

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-14359-4.pdf

Reference33 articles.

1. Bertsekas D, Tsitsiklis J (1997) Parallel and distributed computation: Numerical methods. Athena Scientific, Belmont

2. Bonettini S, Benfenati A, Ruggiero V (2014) Primal-dual first order methods for total variation image restoration in presence of Poisson noise. IEEE Int conf Image Process. 4156–4160

3. Bredies K, Dong Y, Hintermüller M (2013) Spatially dependent regularization parameter selection in total generalized variation models for image restoration. Int J Comput Math 90(1):109–123

4. Bredies K, Holler M (2013) A TGV regularized wavelet based zooming model. Int Conf Scal Spac Vari Meth Comput Vis. 149–160

5. Bredies K, Holler M (2020) Higher-order total variation approaches and generalisations. Inverse Probl 36(12):123001

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