An algorithm for hybrid regularizers based image restoration with Poisson noise

Cong Thang Pham; Thi Thu Thao Tran

Kybernetika (2021)

  • Volume: 57, Issue: 3, page 446-473
  • ISSN: 0023-5954

Abstract

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In this paper, a hybrid regularizers model for Poissonian image restoration is introduced. We study existence and uniqueness of minimizer for this model. To solve the resulting minimization problem, we employ the alternating minimization method with rigorous convergence guarantee. Numerical results demonstrate the efficiency and stability of the proposed method for suppressing Poisson noise.

How to cite

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Pham, Cong Thang, and Tran, Thi Thu Thao. "An algorithm for hybrid regularizers based image restoration with Poisson noise." Kybernetika 57.3 (2021): 446-473. <http://eudml.org/doc/298206>.

@article{Pham2021,
abstract = {In this paper, a hybrid regularizers model for Poissonian image restoration is introduced. We study existence and uniqueness of minimizer for this model. To solve the resulting minimization problem, we employ the alternating minimization method with rigorous convergence guarantee. Numerical results demonstrate the efficiency and stability of the proposed method for suppressing Poisson noise.},
author = {Pham, Cong Thang, Tran, Thi Thu Thao},
journal = {Kybernetika},
keywords = {total variation; image denoising; image deblurring; alternating minimization method},
language = {eng},
number = {3},
pages = {446-473},
publisher = {Institute of Information Theory and Automation AS CR},
title = {An algorithm for hybrid regularizers based image restoration with Poisson noise},
url = {http://eudml.org/doc/298206},
volume = {57},
year = {2021},
}

TY - JOUR
AU - Pham, Cong Thang
AU - Tran, Thi Thu Thao
TI - An algorithm for hybrid regularizers based image restoration with Poisson noise
JO - Kybernetika
PY - 2021
PB - Institute of Information Theory and Automation AS CR
VL - 57
IS - 3
SP - 446
EP - 473
AB - In this paper, a hybrid regularizers model for Poissonian image restoration is introduced. We study existence and uniqueness of minimizer for this model. To solve the resulting minimization problem, we employ the alternating minimization method with rigorous convergence guarantee. Numerical results demonstrate the efficiency and stability of the proposed method for suppressing Poisson noise.
LA - eng
KW - total variation; image denoising; image deblurring; alternating minimization method
UR - http://eudml.org/doc/298206
ER -

References

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