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Wanxue Wei 1,2†Muyang Zhang 3†Zhuoqun Yuan 3Weike Wang 3[ ... ]Kebin Shi 1,2,4,5,7,*
Author Affiliations
Abstract
1 State Key Laboratory of Mesoscopic Physics and Frontiers Science Center for Nano-optoelectronics, School of Physics, Peking University, Beijing 100871, China
2 National Biomedical Imaging Center, Peking University, Beijing 100871, China
3 Institute of Modern Optics, Nankai University, Tianjin Key Laboratory of Micro-Scale Optical Information Science and Technology, Tianjin 300350, China
4 Collaborative Innovation Center of Extreme Optics, Shanxi University, Taiyuan 030006, China
5 Peking University Yangtze Delta Institute of Optoelectronics, Nantong 226010, China
6 e-mail: ymliang@nankai.edu.cn
7 e-mail: kebinshi@pku.edu.cn
Multi-angle illumination is a widely adopted strategy in various super-resolution imaging systems, where improving computational efficiency and signal-to-noise ratio (SNR) remains a critical challenge. In this study, we propose the integration of the iterative kernel correction (IKC) algorithm with a multi-angle (MA) illumination scheme to enhance imaging reconstruction efficiency and SNR. The proposed IKC-MA scheme demonstrates the capability to significantly reduce image acquisition time while achieving high-quality reconstruction within 1 s, without relying on extensive experimental datasets. This ensures broad applicability across diverse imaging scenarios. Experimental results indicate substantial improvements in imaging speed and quality compared to conventional methods, with the IKC-MA model achieving a remarkable reduction in data acquisition time. This approach offers a faster and more generalizable solution for super-resolution microscopic imaging, paving the way for advancements in real-time imaging applications.
Photonics Research
2025, 13(7): 1973
 
作者单位
摘要
南开大学现代光学研究所, 天津 300350
包含多波长信息的低分辨(LR)灰度图难以被完全解复用,根据LR图像信息重建出的彩色高分辨(HR)图像容易出现通道串扰的现象。为重建不受通道串扰干扰的彩色HR图像,提出一种基于三维卷积神经网络(CNN)的彩色HR图像重建算法。采用主成分分析法提取单色HR图像和彩色LR图像的结构信息,然后基于结构信息训练CNN来建立单色HR图像和彩色LR图像之间的映射关系,最后生成彩色HR图像。实验结果表明,所提算法可以获得不受通道串扰影响、色彩不失真的彩色HR图像。定量评价指标方均根误差小于0.1,结构相似性参数大于0.9。
成像系统 显微术 傅里叶叠层显微成像 卷积神经网络 主成分分析 彩色图像重建 
光学学报
2020, 40(20): 2011001

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