Suppressing meta-holographic artifacts by laser coherence tuning

Calibration technique for suppressing residual etalon artifacts in slit-averaged Raman spectroscopy

Back-illuminated charged-coupled device (BI-CCD) arrays increase quantum efficiency but also amplify etaloning, a multiplicative, wavelength-dependent fixed-pattern effect. When spectral data from hundreds of BI-CCD rows are combined, the averaged spectrum will generally appear etalon-free. This can mask substantial etaloning at the row level, even if the BI-CCD has been treated to suppress the effect. This Note compares two methods of etalon correction, one with simple averaging and one with row-by-row calibration using a fluorescence standard. Two BI-CCD arrays, both roughened by the supplie…

漫射照明全息光学相干断层扫描

Diffuse-illumination holographic optical coherence tomography

本研究提出一种漫射照明全息OCT技术，通过非相干平均变化漫射照明体积，有效抑制多次散射散斑和空间相干噪声，显著提升图像质量，并在标准OCT应用轴向范围内保留全息重建能力。

混合频谱-空间域配准用于数字在线全息显微镜中的纳米级跟踪

Hybrid spectral-spatial domain registration for nanometric tracking in digital in-line holographic microscopy

提出混合频谱-空间域（HSSD）框架，结合DFT粗估计与Lucas-Kanade精化，实现数字在线全息显微镜中宽捕获范围下的纳米级亚像素位移跟踪。

Deep learning-based color holographic microscopy

We report a framework based on a generative adversarial network (GAN) that performs high-fidelity color image reconstruction using a single hologram of a sample that is illuminated simultaneously by light at three different wavelengths. The trained network learns to eliminate missing-phase-related artifacts, and generates an accurate color transformation for the reconstructed image. Our framework is experimentally demonstrated using lung and prostate tissue sections that are labeled with different histological stains. This framework is envisaged to be applicable to point-of-care histopathology…

基于旋转扩散器相干噪声抑制的无透镜数字全息显微镜实验优化

Experimental optimization of lensless digital holographic microscopy with rotating diffuser-based coherent noise reduction

提出一种结合旋转扩散器抑制相干噪声的无透镜数字全息显微镜方法，经硬件优化实现高达50%噪声降低，并保持高分辨率，适用于高通量无染色生物医学成像。

Computer-free, all-optical reconstruction of holograms using diffractive networks

Reconstruction of in-line holograms of unknown objects in general suffers from twin-image artifacts due to the appearance of an out-of-focus image overlapping with the desired image to be reconstructed. Computer-based iterative phase retrieval algorithms and learning-based methods have been used for the suppression of such image artifacts in digital holography. Here we report an all-optical hologram reconstruction method that can instantly retrieve the image of an unknown object from its in-line hologram and eliminate twin-image artifacts without using a digital processor or a computer. Multip…