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

被引:86
作者
Chen, Chun [1 ]
Lee, Byounghyo [1 ]
Li, Nan-Nan [2 ,3 ]
Chae, Minseok [1 ]
Wang, Di [2 ,3 ]
Wang, Qiong-Hua [2 ,3 ]
Lee, Byoungho [1 ]
机构
[1] Seoul Natl Univ, Sch Elect & Comp Engn, Gwanakro 1, Seoul 08826, South Korea
[2] Beihang Univ, Sch Instrumentat & Optoelect Engn, Beijing 100191, Peoples R China
[3] Beihang Univ, Beijing Adv Innovat Ctr Big Data Based Precis Med, Beijing 100191, Peoples R China
基金
中国国家自然科学基金; 新加坡国家研究基金会;
关键词
ITERATIVE ALGORITHM; PHASE RETRIEVAL; DISPLAY; KINOFORM;
D O I
10.1364/OE.425077
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
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
引用
收藏
页码:15089 / 15103
页数:15
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