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Bayesian regularization restoration algorithm for photon counting images

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Abstract

The photon counting image collected under 10− 4 lux environment has a degraded image quality due to background noises and other problems. Bayesian estimation is a classical approach for photon counting image restoration and regularization has also been widely used in image processing. However, the regularization method is not suitable for photon counting images with extremely lack of information, and the recovery effect of Bayesian estimation in images mixed with unknown noise is not ideal. The main contribution of this paper is that on the basis of Bayesian estimation, the regularization method is introduced to solve the problem of restoring photon counting images mixed with unknown noise under 10− 4 lux environment. The original part is that the gamma distribution of the expected value of photon counting is used as its prior condition, and the error function is expressed as the form of the norm to establish the objective function. Through an approximate iterative solution, the optimal estimation of the photon counting expectation is carried out to achieve the optimal restoration of the photon counting image. Experiments demonstrate that the background noise is effectively removed and the image quality is improved after restoring photon counting images. Also, the final result of the proposed method is superior to other comparative methods in multiple evaluation indexes and achieved better effects.

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Acknowledgements

This research was funded by the Natural Science Foundation project of Shandong Province in 2020 (Research on 3D Integrated Imaging Technology based on Photon counting Method), the National Natural Science Foundation of China, grant number 61801272 and the SDUT and Zibo District Integration Project, grant number 2019ZBXC516.

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Correspondence to Liju Yin.

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Li, Y., Yin, L., Wang, Z. et al. Bayesian regularization restoration algorithm for photon counting images. Appl Intell 51, 5898–5911 (2021). https://doi.org/10.1007/s10489-020-02175-4

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