Author Affiliations
Abstract
1 Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou 570228, P. R. China
2 School of Computer Science and Technology, Hainan University, Haikou 570228, P. R. China
3 Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, P. R. China
Quantitative data analysis in single-molecule localization microscopy (SMLM) is crucial for studying cellular functions at the biomolecular level. In the past decade, several quantitative methods were developed for analyzing SMLM data; however, imaging artifacts in SMLM experiments reduce the accuracy of these methods, and these methods were seldom designed as user-friendly tools. Researchers are now trying to overcome these difficulties by developing easy-to-use SMLM data analysis software for certain image analysis tasks. But, this kind of software did not pay sufficient attention to the impact of imaging artifacts on the analysis accuracy, and usually contained only one type of analysis task. Therefore, users are still facing difficulties when they want to have the combined use of different types of analysis methods according to the characteristics of their data and their own needs. In this paper, we report an ImageJ plug-in called DecodeSTORM, which not only has a simple GUI for human–computer interaction, but also combines artifact correction with several quantitative analysis methods. DecodeSTORM includes format conversion, channel registration, artifact correction (drift correction and localization filtering), quantitative analysis (segmentation and clustering, spatial distribution statistics and colocalization) and visualization. Importantly, these data analysis methods can be combined freely, thus improving the accuracy of quantitative analysis and allowing users to have an optimal combination of methods. We believe DecodeSTORM is a user-friendly and powerful ImageJ plug-in, which provides an easy and accurate data analysis tool for adventurous biologists who are looking for new imaging tools for studying important questions in cell biology.
Journal of Innovative Optical Health Sciences
2023, 16(6): 2350006
1 中国科学院上海光学精密机械研究所高功率激光单元技术实验室，上海 201800
2 中国科学院大学材料科学与光电工程中心，北京 100049
3 国科大杭州高等研究院物理与光电工程学院，浙江 杭州 310024
4 中国科学技术大学物理学院，安徽 合肥 230026
5 中国科学院力学研究所高温气体动力学国家重点实验室，北京 100190
6 中国科学院大学工程学院，北京 100049
7 中国科学院上海光学精密机械研究所红外光学材料研究中心，上海 201800
针对燃烧诊断在2~3 μm波长的光谱测量需求，设计并搭建了基于反谐振空芯光纤的可调谐半导体吸收光谱（TDLAS）测量装置，开展了高温水汽在2.5 μm波长吸收光谱的定标与测量研究。在2~5 μm中红外波段，反谐振空芯光纤可实现低损、单模长距离传输，能够有效解决商用氟化物光纤多模干涉造成的TDLAS测量精度下降的问题。经所提TDLAS系统准直后光束的直径低至2.5 mm，发散角为0.004 rad，系统信噪比为31 dB，相比基于氟化物光纤的TDLAS系统，所提系统的性能得到了极大提升。进一步分析了反谐振空芯光纤中痕量水蒸气对于4029.52 cm-1谱线测量的影响，并通过抽真空的方式降低其影响，从而提高了系统的测量精度。
光纤 反谐振空芯光纤 激光吸收光谱 多模干涉 单模 燃烧诊断 光学学报
2023, 43(13): 1306005
1 中国科学院福建物质结构研究所, 福州 350002
2 中国科学院大学, 北京 100039
随着电子信息技术的飞速发展, 具有更高抗干扰能力以及更高灵敏度的日盲紫外探测器引起了广泛关注。六方相氮化硼(h-BN)凭借其超宽带隙、高光吸收系数、高热导率及高击穿场强等优势成为日盲紫外探测器研究的热点材料。此外, h-BN良好的机械强度和光学透明性使其兼具柔性探测器的潜力。然而室温条件下制备的h-BN薄膜常具有较多缺陷, 极大程度上限制了其柔性探测器的发展。本文在室温条件下采用反应磁控溅射, 以B为生长源, 在蓝宝石和Si衬底上实现了较高质量h-BN薄膜的制备, 并在此薄膜的基础上制备了高性能日盲紫外探测器。3 V电压下, 其探测器拥有极低的暗电流(0.07 pA)、较高的响应度(1.37 μA/W)和探测率(2.73×1010 Jones)。本文的研究结果证实了室温制备h-BN薄膜及其日盲紫外探测器的可行性, 为实现可在室温下工作的h-BN探测器的应用提供了参考。
h-BN薄膜 反应溅射法 室温 日盲紫外探测器 光电性能 响应度 h-BN film reactive sputtering method room temperature solar-blind ultraviolet detector photoelectric property responsivity
Author Affiliations
Abstract
1 School of Physical Sciences, University of Science and Technology of China, Hefei 230026, China
2 Key Laboratory of High Power Laser Materials, Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai 201800, China
3 Accelink Technologies Co., Wuhan 430000, China
4 Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
5 College of Materials Science and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing 100049, China
In this Letter, the optical amplification characteristics of the home-made Bi/P co-doped silica fiber were systematically explored in the range of 1270–1360 nm. The maximum gain of 24.6 dB was obtained in the single-pass amplification device, and then improved to 38.3 dB in the double-pass amplification device for signal power. In addition, we simultaneously investigated the laser performance of the fiber with the linear cavity. A slope efficiency of 16.4% at was obtained with a maximum output power of about 133 mW under the input pump power of 869 mW at 1240 nm. As far as we know, it is the first laser reported based on the bismuth-doped fiber in China.
Bi/P co-doped silica fiber fiber amplifier O-band amplification fiber laser Chinese Optics Letters
2023, 21(5): 050601
本文通过固结磨料球与KDP晶体对磨的单因素试验探究固结磨料球中反应物种类、磨粒浓度、反应物浓度、基体硬度对摩擦系数、磨痕截面积和磨痕处粗糙度的影响，试验结果表明：KHCO3固结磨料球对磨后磨痕对称性好，磨痕处的粗糙度值低；磨痕截面积随磨粒和反应物浓度的增加而增大，随基体硬度的增大而降低；磨痕处粗糙度随磨粒和反应物浓度的增加先降低后上升，随基体硬度的增大先上升后降低；摩擦系数受磨粒和反应物浓度影响不明显，随基体硬度的增大而降低。选择KHCO3作为反应物，Ⅰ基体，磨粒浓度为基体质量的100%，反应物浓度为15%制备固结磨料球与KDP晶体对磨后的磨痕轮廓对称度好且磨痕处粗糙度值低，以该组分制备固结磨料垫干式抛光KDP晶体，可实现晶体表面粗糙度Sa值为18.50 nm，材料去除率为130 nm/min的高效精密加工。
KDP晶体 固结磨料垫 晶体加工 干式抛光 摩擦磨损 反应物 KDP crystal fixed abrasive pad crystal machining dry polishing friction and wear reactant
为了在红外成像系统中实现高效的自动对焦功能，深入分析和讨论了红外成像系统中自动对焦功能的优化方法及特点。结合具体的工程化应用，提出了一种对图像清晰度评价函数局部随机起伏噪声的估计方法，该方法可以提高自动对焦功能的可靠性，通过将图像清晰度评价函数的灵敏度作为反馈量引入爬坡过程，优化了爬坡算法的收敛速度。其优化方法在工程应用中的实施效果，验证了设计的正确性，优化方法的有效性。
自动对焦 红外成像 图像清晰度评价函数 爬坡算法 自动对焦窗口 auto-focusing, infrared imaging system, image shar
在红外图像拼接技术的实际应用中，除了追求较高的拼接精度外，还应尽可能地提高拼接速度以满足实时性的要求。本文结合红外图像拼接技术的实际应用需求，将BRISK 二值描述子和Canny边缘检测应用于SURF 红外图像拼接，提出一种改进的SURF 红外图像拼接方法。改进的红外图像拼接方法在特征点提取阶段将SURF 特征点检测、Canny 边缘检测和BRISK 二值描述子有效结合，生成边缘SURF-BRISK 特征点；在特征点匹配阶段采用自适应阈值的层次聚类方法作为搜索策略，并采用RANSAC 算法剔除误匹配的特征点；在图像融合阶段采用渐入渐出的融合方法消除图像拼接缝隙。实验证明，本文所用红外图像拼接方法在对复杂场景下的红外图像进行拼接时，有效地提高了配准精度和拼接速度。
红外图像拼接 边缘SURF-BRISK 特征点 层次聚类 infrared image mosaic edge SURF-BRISK feature Hierarchical clustering
1 昆明物理研究所, 云南昆明 650223
2 微光夜视技术重点实验室, 陕西西安 710068
由于红外与微光图像成像原理的不同, 成像特征的巨大差异, 研究提出了一种基于点特征与 Freeman链码的红外与微光图像配准算法。目的是解决红外与微光图像配准中特征点提取较复杂、特征匹配难的问题; 采用优化的 Harris角点检测算法进行特征点提取, 结合环形灰度区域、RSTC不变矩和 Freeman链码对红外与微光图像进行特征点匹配。实验结果表明该算法能够提取出有效的匹配点, 能够有效地解决红外与微光图像配准中遇到的视场不统一、旋转、平移问题。
红外/微光图像 Harris角点检测 RSTC不变矩 特征多边形 Freeman链码 infrared and low light level image Harris corner detection RSTC invariant moments polygon of feature points freeman chain code
在研究红外图像成像原理与特征、传统红外图像配准方法的基础上, 提出了一种改进的联合点特征与灰度特征的红外图像配准算法。首先采用经典的 Harris角点检测算法提取一次角点, 在一次角点的基础上对其进行下降排序, 对排序结果进行不同份数的等分并提取每一部分的中间值, 最后根据图像配准需求有效利用中值选择不同的特征点; 该算法充分利用环形区域的旋转不变性和特征点区域灰度差异性很小的原则进行特征点匹配。实验结果表明该算法能够提取出更加精确的匹配点, 能够有效的完成红外图像配准。
红外图像 Harris角点检测 灰度区域 图像配准 infrared image Harris corner detection gray region image registration
