Light-field fluorescence microscopy (LFM) is a powerful elegant compact method for long-term high-speed imaging of complex biological systems, such as neuron activities and rapid movements of organelles. LFM experiments typically generate terabytes of image data and require a substantial amount of storage space. Some lossy compression algorithms have been proposed recently with good compression performance. However, since the specimen usually only tolerates low-power density illumination for long-term imaging with low phototoxicity, the image signal-to-noise ratio (SNR) is relatively low, which will cause the loss of some efficient position or intensity information using such lossy compression algorithms. Here, we propose a phase-space continuity-enhanced bzip2 (PC-bzip2) lossless compression method for LFM data as a high-efficiency and open-source tool that combines graphics processing unit-based fast entropy judgment and multicore-CPU-based high-speed lossless compression. Our proposed method achieves almost 10% compression ratio improvement while keeping the capability of high-speed compression, compared with the original bzip2. We evaluated our method on fluorescence beads data and fluorescence staining cells data with different SNRs. Moreover, by introducing temporal continuity, our method shows the superior compression ratio on time series data of zebrafish blood vessels.

Structure illumination microscopy (SIM) imposes no special requirements on the fluorescent dyes used for sample labeling, yielding resolution exceeding twice the optical diffraction limit with low phototoxicity, which is therefore very favorable for dynamic observation of live samples. However, the traditional SIM algorithm is prone to artifacts due to the high signal-to-noise ratio (SNR) requirement, and existing deep-learning SIM algorithms still have the potential to improve imaging speed. Here, we introduce a deep-learning-based video-level and high-fidelity super-resolution SIM reconstruction method, termed video-level deep-learning SIM (VDL-SIM), which has an imaging speed of up to 47 frame/s, providing a favorable observing experience for users. In addition, VDL-SIM can robustly reconstruct sample details under a low-light dose, which greatly reduces the damage to the sample during imaging. Compared with existing SIM algorithms, VDL-SIM has faster imaging speed than existing deep-learning algorithms, and higher imaging fidelity at low SNR, which is more obvious for traditional algorithms. These characteristics enable VDL-SIM to be a useful video-level super-resolution imaging alternative to conventional methods in challenging imaging conditions.

为了满足荧光显微镜技术对多波长单模耦合输出激光的需求，研究了400~680 nm内多波长激光耦合进单模光纤的技术，设计了三片式耦合透镜组很好地消除了不同波长耦合时的色差以提高耦合效率，同时考虑光纤耦合调试难度大的问题，设计了能快速简单完成耦合调节的耦合光纤部件结构以及耦合调试的方法，通过实验测试荧光成像常用的4种波段激光（405，488，561，638 nm），耦合效率均大于65%。实验结果达到了较高的光纤耦合水平，证明该多波长激光耦合器性能优异。同时，由于耦合器装调简单且成本低，本文的工作具有进一步商业化的价值，且为多波长单模耦合激光器国产化打下了坚实的基础。

为解决原子力显微镜（Atomic Force Microscope， AFM）系统更换探针后光路调整复杂耗时、精度不足的问题，本文首次提出通过精密控制探针与探针夹装配位置来实现更换的探针相对AFM系统原光路位置的一致，进而实现免去AFM系统换针后调整光路步骤。该系统的光路一致性组件采用光束偏转法对探针位置与偏转进行放大与监测，并使用高精度位移与角度调节平台进行探针相对于探针夹的方位调整。通过实物搭建对探针一致性效果进行了验证，并对紫外光（Ultraviolet， UV）胶水固化过程导致探针位置偏移影响；探针不同偏移量时产生的探测器噪音对AFM系统成像质量影响进行了系统分析。实验结果表明：经由该系统装配的探针平均位置精度接近1.1 µm；并且在AFM系统中更换一致性探针仅需8 s。该系统实现了高精度且质量稳定的探针一致性装配，极大地简化了AFM系统重新校准光路的操作步骤，其与自动换针装置配合可有效提升工业计量型AFM的操作与测量性能。

The 3D location and dipole orientation of light emitters provide essential information in many biological, chemical, and physical systems. Simultaneous acquisition of both information types typically requires pupil engineering for 3D localization and dual-channel polarization splitting for orientation deduction. Here we report a geometric phase helical point spread function for simultaneously estimating the 3D position and dipole orientation of point emitters. It has a compact and simpler optical configuration compared to polarization-splitting techniques and yields achromatic phase modulation in contrast to pupil engineering based on dynamic phase, showing great potential for single-molecule orientation and localization microscopy.