Hybrid total variation and L0-norm regularized non-blind deconvolution for Poissonian blurred image restoration

Chenlong Zhu; Yannan Yang; Wende Dong

doi:10.1117/12.3014983

30 April 2024 Hybrid total variation and L₀-norm regularized non-blind deconvolution for poissonian blurred image restoration

Chenlong Zhu, Yannan Yang, Wende Dong

Author Affiliations +

Proceedings Volume 13155, Sixth Conference on Frontiers in Optical Imaging and Technology: Novel Imaging Systems; 131550C (2024) https://doi.org/10.1117/12.3014983
Event: Sixth Conference on Frontiers in Optical Imaging Technology and Applications (FOI2023), 2023, Nanjing, JS, China

Abstract

In the fields of astronomical observation and fluorescence microscopic imaging, the obtained image is usually degraded by blur effects and Poisson noise. In this paper, we propose a robust hybrid regularization method consisting of total variation and L0-norm of image gradients and combine it with the Poisson distribution to formulate this kind of ill-posed problem. We also propose an efficient alternately minimization algorithm based on variable splitting and Lagrange multipliers to find the optimal solution, which can transform the original problem into a regularized deconvolution problem with quadratic fidelity term and a simple convex optimization problem. In the end, we carry out experiments to prove its convergence and effectiveness, the results show that the proposed method is stable, efficient and the quality of the restored image is comparable with some state-of-the-art methods.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chenlong Zhu, Yannan Yang, and Wende Dong "Hybrid total variation and L₀-norm regularized non-blind deconvolution for poissonian blurred image restoration", Proc. SPIE 13155, Sixth Conference on Frontiers in Optical Imaging and Technology: Novel Imaging Systems, 131550C (30 April 2024); https://doi.org/10.1117/12.3014983

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