Machine learning can effectively accelerate the runtime of a computer-generated hologram.However,the angular spectrum method and single fast Fresnel transform-based machine learning acceleration algorithms are still l...Machine learning can effectively accelerate the runtime of a computer-generated hologram.However,the angular spectrum method and single fast Fresnel transform-based machine learning acceleration algorithms are still limited in the field-of-view angle of projection.In this paper,we propose an efficient method for the fast generation of large field-of-view holograms combining stochastic gradient descent(SGD),neural networks,and double-sampling Fresnel diffraction(DSFD).Compared with the traditional Gerchberg-Saxton(GS)algorithm,the DSFD-SGD algorithm has better reconstruction quality.Our neural network can be automatically trained in an unsupervised manner with a training set of target images without labels,and its combination with the DSFD can improve the optimization speed significantly.The proposed DSFD-Net method can generate 2000-resolution holograms in 0.05 s.The feasibility of the proposed method is demonstrated with simulations and experiments.展开更多
基金This work was supported by the National Natural Science Foundation of China(No.61975122)the National Key Research and Development Program of China(No.2018YFA0701802).
文摘Machine learning can effectively accelerate the runtime of a computer-generated hologram.However,the angular spectrum method and single fast Fresnel transform-based machine learning acceleration algorithms are still limited in the field-of-view angle of projection.In this paper,we propose an efficient method for the fast generation of large field-of-view holograms combining stochastic gradient descent(SGD),neural networks,and double-sampling Fresnel diffraction(DSFD).Compared with the traditional Gerchberg-Saxton(GS)algorithm,the DSFD-SGD algorithm has better reconstruction quality.Our neural network can be automatically trained in an unsupervised manner with a training set of target images without labels,and its combination with the DSFD can improve the optimization speed significantly.The proposed DSFD-Net method can generate 2000-resolution holograms in 0.05 s.The feasibility of the proposed method is demonstrated with simulations and experiments.
