Multi-depth hologram generation using stochastic gradient descent algorithm with complex loss function

The stochastic gradient descent (SGD) method is useful in the phase-only hologram optimization process and can achieve a high-quality holographic display. However, for the current SGD solution in multi-depth hologram generation, the optimization time increases dramatically as the number of depth layers of object increases, leading to the SGD method nearly impractical in hologram generation of the complicated three-dimensional object. In this paper, the proposed method uses a complex loss function instead of an amplitude-only loss function in the SGD optimization process. This substitution ensures that the total loss function can be obtained through only one calculation, and the optimization time can be reduced hugely. Moreover, since both the amplitude and phase parts of the object are optimized, the proposed method can obtain a relatively accurate complex amplitude distribution. The defocus blur effect is therefore matched with the result from the complex amplitude reconstruction. Numerical simulations and optical experiments have validated the effectiveness of the proposed method. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

Automated summary

The proposed method in this paper utilizes a complex loss function instead of an amplitude-only loss function in the stochastic gradient descent (SGD) optimization process, resulting in improved efficiency and accuracy in hologram generation.