基于深度学习的复合贝塞尔高斯光束大气湍流效应补偿

Du Qianqian, 杜芊芊; Wei Hongyan, 韦宏艳; Shi Chenyin, 史晨寅; Xue Xiaolei, 薛晓磊; Jia Peng, 贾鹏

doi:10.3788/cjl221444

Chin. J. Laser

2023

DOI: 10.3788/cjl221444

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基于深度学习的复合贝塞尔高斯光束大气湍流效应补偿

杜芊芊 Du Qianqian,

韦宏艳 Wei Hongyan,

史晨寅 Shi Chenyin

et al.

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2024

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Cited by 6 publications

References 18 publications

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Degraded image restoration of vortex beam array based on deep learning

Zhao,

Wei,

et al. 2024

Phys. Scr.

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The phase aberration and intensity fluctuation of the vortex beam array caused by atmospheric turbulence decrease the decoding accuracy of the optical communication system. This paper proposes an end-to-end turbulence-degraded image restoration method based on deep learning to solve the problem. The K-means clustering algorithm is employed to obtain the coordinate information of each beam in the array, and the distorted vortex beam array is segmented. The neural network constructed is used to restore the degraded image of a single vortex beam obtained by segmentation. Then the restored intensity image of the vortex beam array is obtained by combining the existing coordinate information. The simulation results show that the intensity correlation coefficients of the 3 × 3 rectangular distribution Laguerre–Gaussian beam arrays are increased to more than 0.99 after restoring from 1000 meters of transmission in both varied and unknown turbulence intensities, alongside differing CCD signal-to-noise ratios. This method does not require wavefront reconstruction, which further improves the restoration speed and saves computational resources, and has good generalization ability and robustness in quickly restoring the distorted light intensity of vortex beams. The results provide a theoretical basis for studying atmospheric turbulence influence mitigation techniques for vortex optical communication.

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Degraded image restoration of vortex beam array based on deep learning

Zhao,

Wei,

et al. 2024

Phys. Scr.

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大气湍流中两条相关刃型位错的相互作用

Chen Haitao,

Yang Huajun,

Gao Zenghui

et al. 2024

光学学报

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基于混合神经网络的紫外光散射信道盲均衡方法

Zhao Taifei,

Sun Yuxin,

Pan Feixiang

et al. 2024

光学学报

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基于深度学习的复合贝塞尔高斯光束大气湍流效应补偿

Cited by 6 publications

References 18 publications

Degraded image restoration of vortex beam array based on deep learning

Degraded image restoration of vortex beam array based on deep learning

大气湍流中两条相关刃型位错的相互作用

基于混合神经网络的紫外光散射信道盲均衡方法

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