Generative adversarial neural network for 3D-hologram reconstruction

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2024-02-14 DOI:10.1088/1612-202x/ad26eb

Semen A Kiriy, Dmitry A. Rymov, Andrey S. Svistunov, A. Shifrina, R. Starikov, P. Cheremkhin

引用次数: 0

Abstract

Neural-network-based reconstruction of digital holograms can improve the speed and the quality of micro- and macro-object images, as well as reduce the noise and suppress the twin image and the zero-order. Usually, such methods aim to reconstruct the 2D object image or amplitude and phase distribution. In this paper, we investigated the feasibility of using a generative adversarial neural network to reconstruct 3D-scenes consisting of a set of cross-sections. The method was tested on computer-generated and optically-registered digital inline holograms. It enabled the reconstruction of all layers of a scene from each hologram. The reconstruction quality is improved 1.8 times when compared to the U-Net architecture on the normalized standard deviation value.

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用于三维全息图重建的生成对抗神经网络

基于神经网络的数字全息图像重建可以提高微观和宏观物体图像的速度和质量，还可以降低噪声、抑制孪生图像和零阶。通常，这类方法旨在重建二维物体图像或振幅和相位分布。在本文中，我们研究了使用生成对抗神经网络重建由一组横截面组成的三维场景的可行性。该方法在计算机生成和光学注册的数字内嵌全息图上进行了测试。它能够从每张全息图中重建场景的所有层次。在归一化标准偏差值方面，与 U-Net 架构相比，重建质量提高了 1.8 倍。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.