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相关概念视频

Deconvolution01:20

Deconvolution

414
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
414
Phase Contrast and Differential Interference Contrast Microscopy01:26

Phase Contrast and Differential Interference Contrast Microscopy

11.4K
Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...
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相关实验视频

Updated: Nov 19, 2025

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator
08:39

Shaping the Amplitude and Phase of Laser Beams by Using a Phase-only Spatial Light Modulator

Published on: January 28, 2019

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基于深度学习的不规则形状光圈的单干扰图的相位检索.

Ying Li, Xin Liu, Zhongming Yang

    Optics express
    |November 29, 2023
    PubMed
    概括

    这项研究引入了一种深度学习方法,用于精确地从干扰图中检索相位,即使有不规则的光圈. 该技术准确地重建波浪,为光学表面测量提供了传统干扰测量的强大替代方案.

    科学领域:

    • 光学计量学 在光学计量学
    • 计算光学是指计算机光学.
    • 在光学领域的人工智能.

    背景情况:

    • 阶段检索对于光学表面的表征至关重要.
    • 传统的方法与不规则的光圈和噪音作斗争.
    • 泽尼克多项式被广泛用于波面分解.

    研究的目的:

    • 开发使用深度学习的高精度相位检索方法.
    • 从不规则光圈的单干涉图中提取泽尼克系数.
    • 为了使复杂的光学表面能够准确地检索相位分布.

    主要方法:

    • 训练了一个深度学习模型来提取泽尼克系数.
    • 使用泽尼克多项式重建了相位分布.
    • 在各种噪音条件下进行模拟和实验.

    主要成果:

    • 在不规则的光圈中,实现了10-3λ级的波面误差.
    • 证明了高的测量准确性和对噪声的强度.
    • 实验准确度与商业相位移干扰仪相当.

    结论:

    • 拟议的深度学习方法为不规则的光圈提供了高精度的相位检索.

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  • 这种技术为光学表面计量学提供了强大而准确的解决方案.
  • 它对于具有非标准光圈形状的光学表面特别有用.