多光谱图像
光学
显微镜
计算
压缩传感
工作流程
数据采集
计算机视觉
迭代重建
像素
计算机科学
算法
物理
人工智能
数据库
操作系统
作者
Alberto Ghezzi,Andrea Farina,Vito Vurro,Andrea Bassi,Gianluca Valentini,Cosimo D’Andrea
出处
期刊:Optics Letters
[Optica Publishing Group]
日期:2023-11-27
卷期号:49 (2): 278-278
被引量:2
摘要
A single-pixel camera combined with compressive sensing techniques is a promising fluorescence microscope scheme for acquiring a multidimensional dataset (space, spectrum, and lifetime) and for reducing the measurement time with respect to conventional microscope schemes. However, upon completing the acquisition, a computational step is necessary for image reconstruction and data analysis, which can be time-consuming, potentially canceling out the beneficial effect of compressive sensing. In this work, we propose and experimentally validate a fast-fit workflow based on global analysis and multiple linear fits, which significantly reduces the computation time from tens of minutes to less than 1 s. Moreover, as the method is interlaced with the measurement flow, it can be applied in parallel with the acquisitions.
科研通智能强力驱动
Strongly Powered by AbleSci AI