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相关概念视频

Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

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Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
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Confocal Fluorescence Microscopy01:16

Confocal Fluorescence Microscopy

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Confocal microscopy is an advanced microscopic technique. The prime advantage of the confocal microscope over other microscopy techniques is its ability to block the out-of-focus light from the illuminated samples using pinholes. It is widely used with fluorescence optics to obtain high-resolution, sharp contrast images. Unlike optical microscopes, confocal microscopes use a focused beam of light laser to scan the entire sample surface at different z-planes. These microscopes are, therefore,...
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基于图像的高动态范围结构光的精确3D重建

Hao Wang, Chaobo Zhang, Xiang Qian

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |August 25, 2025
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    概括

    本研究提出了使用结构光的高动态范围 (HDR) 3D重建的深度学习管道. 它有效地捕捉HDR边缘图案,使具有具有挑战性的反射表面的对象能够进行精确的3D测量.

    科学领域:

    • 光学和光学
    • 计算机视觉
    • 测量学

    背景情况:

    • 具有不同表面反射率的物体的精确3D重建,特别是在边缘投影形状测量中,需要高动态范围 (HDR) 成像.
    • 由于有限的动态范围,单曝光摄像头难以有效地捕捉HDR边缘图案,从而阻碍精确的3D测量.
    • 现有的方法通常需要多次曝光或复杂的设置,增加获取时间和系统复杂性.

    研究的目的:

    • 开发一个高效准确的基于深度学习的HDR结构光3D重建管道.
    • 解决单曝光摄像机在3D测量中捕获HDR边缘图案方面的局限性.
    • 为了实现具有挑战性的HDR反射表面的对象的强大而精确的3D重建.

    主要方法:

    • 开发了一个端到端的深度学习管道,包括HDR边缘生成模块和阶段计算模块.
    • HDR边缘生成模块使用注意力引导和特征蒸从短和长曝光低动态范围 (LDR) 输入中重建HDR边缘图像.
    • 阶段计算模块处理生成的HDR边缘的阶段信息进行3D重建.

    主要成果:

    • 拟议的方法在金属HDR数据集上实现了0.105的相位误差,与多次曝光相位移形计 (PSP) 相似,但投影时间显著缩短 (8.3%).
    • 定量测量显示各种物体的精度低于50%,包括陶球,平板和金属步骤.

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  • 除研究证实了特征蒸和注意力机制在生成高质量的HDR边缘图案中的有效性.
  • 作为HDR结构光测量的基准,创建了一个新的HDR成像金属数据集,包含1700个样本.

    • 结论:

    • 深度学习管道为HDR结构光3D重建提供了高效和可通用的解决方案.
    • 该方法在各种物体几何形状,曝光水平和具有挑战性的全球照明条件中表现出强度.
    • 开发的方法显著提高了具有HDR反射表面的对象3D重建的效率和准确性.