利用基于菲涅耳的无监督神经网络实现任意像素传播的高动态范围平面摄影。

IF 3.3 2区物理与天体物理 Q2 OPTICS

Optics express Pub Date : 2025-09-08 DOI:10.1364/OE.569210

Zexu Liu, Yunyi Chen, Nan Lin

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引用次数: 0

摘要

平面摄影是一种无透镜相位检索技术，广泛应用于材料科学、生物成像和半导体检测等领域。然而，平面摄影的实际分辨率受到两个因素的限制：一是由实验装置决定的重构像素尺寸，二是由于探测器受井深限制导致的有效数值孔径（NA）受限。为了解决这些问题，我们提出了使用基于菲涅耳的无监督神经网络进行任意像素大小（funaps）传播的高动态范围平面摄影。这种新方法实现了具有像素大小调整的高效NA，展示了接近分辨率极限的重建。

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High dynamical range ptychography by applying Fresnel-based unsupervised neural network for arbitrary pixel size (FUNNAPS) propagation.

Ptychography is a lensless phase retrieval technique widely used in material science, bioimaging, and semiconductor inspection. However, the practical resolution of ptychography is limited by two factors: the reconstructed pixel size determined by the experimental setup, and the constrained effective numerical aperture (NA) due to the confined well depth of the detector. To address these issues, we propose high dynamical range ptychography using a Fresnel-based unsupervised neural network for arbitrary pixel size (FUNNAPS) propagation. This new approach enables high effective NA with pixel size adjustment, demonstrating reconstruction close to the resolution limit.

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来源期刊

Optics express 物理-光学

CiteScore

6.60

自引率

15.80%

发文量

5182

审稿时长

2.1 months

期刊介绍： Optics Express is the all-electronic, open access journal for optics providing rapid publication for peer-reviewed articles that emphasize scientific and technology innovations in all aspects of optics and photonics.