Improving the quality of light-field data extracted from a hologram using deep learning

IF 1.3 4区 计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC ETRI Journal Pub Date : 2023-07-05 DOI:10.4218/etrij.2022-0441
Dae-youl Park, Joongki Park
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Abstract

We propose a method to suppress the speckle noise and blur effects of the light field extracted from a hologram using a deep-learning technique. The light field can be extracted by bandpass filtering in the hologram's frequency domain. The extracted light field has reduced spatial resolution owing to the limited passband size of the bandpass filter and the blurring that occurs when the object is far from the hologram plane and also contains speckle noise caused by the random phase distribution of the three-dimensional object surface. These limitations degrade the reconstruction quality of the hologram resynthesized using the extracted light field. In the proposed method, a deep-learning model based on a generative adversarial network is designed to suppress speckle noise and blurring, resulting in improved quality of the light field extracted from the hologram. The model is trained using pairs of original two-dimensional images and their corresponding light-field data extracted from the complex field generated by the images. Validation of the proposed method is performed using light-field data extracted from holograms of objects with single and multiple depths and mesh-based computer-generated holograms.

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使用深度学习提高从全息图中提取的光场数据的质量
我们提出了一种利用深度学习技术抑制从全息图中提取的光场的斑点噪声和模糊效应的方法。光场可通过全息图频域的带通滤波提取。由于带通滤波器的通带尺寸有限,当物体远离全息图平面时会产生模糊,同时还包含由三维物体表面的随机相位分布引起的斑点噪声,因此提取的光场空间分辨率较低。这些限制降低了利用提取的光场重新合成的全息图的重建质量。在所提出的方法中,设计了一个基于生成对抗网络的深度学习模型来抑制斑点噪声和模糊,从而提高从全息图中提取的光场的质量。该模型使用原始二维图像对和从图像生成的复场中提取的相应光场数据进行训练。使用从单一深度和多重深度的物体全息图以及基于网格的计算机生成的全息图中提取的光场数据,对所提出的方法进行了验证。
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来源期刊
ETRI Journal
ETRI Journal 工程技术-电信学
CiteScore
4.00
自引率
7.10%
发文量
98
审稿时长
6.9 months
期刊介绍: ETRI Journal is an international, peer-reviewed multidisciplinary journal published bimonthly in English. The main focus of the journal is to provide an open forum to exchange innovative ideas and technology in the fields of information, telecommunications, and electronics. Key topics of interest include high-performance computing, big data analytics, cloud computing, multimedia technology, communication networks and services, wireless communications and mobile computing, material and component technology, as well as security. With an international editorial committee and experts from around the world as reviewers, ETRI Journal publishes high-quality research papers on the latest and best developments from the global community.
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