| 张 进,李 强,王 冠,夏豪杰,杨 纯.傅里叶单像素显微超分辨成像系统设计[J].电子测量与仪器学报,2022,36(1):174-179 |
| 傅里叶单像素显微超分辨成像系统设计 |
| Design of super resolution system for single pixel imagingresults based on Fourier spectrum acquisition |
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| DOI： |
| 中文关键词: 显微成像 单像素成像 深度学习 超分辨 |
| 英文关键词:single pixel imaging microscopic imaging deep learning super resolution |
| 基金项目:国家自然科学基金( 52175504，51927811，51975179)、中央高校基本科研业务费专项资金（PA2021KCPY0027， PA2021GDGP0061）项目资助 |
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| Author | Institution |
| Zhang Jin | 1. School of Instrument Science and Opto-electronics Engineering, Hefei University of Technology，2. Anhui Province Key Laboratory of Measuring Theory and Precision Instrument, Hefei University of Technology, |
| Li Qiang | 1. School of Instrument Science and Opto-electronics Engineering, Hefei University of Technology，2. Anhui Province Key Laboratory of Measuring Theory and Precision Instrument, Hefei University of Technology, |
| Wang Guan | 1. School of Instrument Science and Opto-electronics Engineering, Hefei University of Technology，2. Anhui Province Key Laboratory of Measuring Theory and Precision Instrument, Hefei University of Technology, |
| Xia Haojie | 1. School of Instrument Science and Opto-electronics Engineering, Hefei University of Technology，2. Anhui Province Key Laboratory of Measuring Theory and Precision Instrument, Hefei University of Technology, |
| Yang Chun | 3. Beijing Satellite Manufacturing Co. Ltd. |
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| 中文摘要: |
| 单像素成像因其仅需一个无空间分辨能力的单点探测器即可实现目标物体的空间信息获取重建物体图像,是解决非可
见光波段成像的关键技术。 该技术的发展和应用在高分辨率空间存在数据采集量大,成像慢的问题。 因此,设计了一种傅里叶
单像素显微超分辨成像系统来提高现有单像素显微成像的效率和质量。 首先,搭建了单像素显微超分辨成像系统,引入基于深
度学习的超分辨模型来提升其成像分辨率,从而快速获得高分辨率的物体重建图像。 经实验结果证明,相同的光强信号采集时
间下,成像分辨率可提高近 9 倍,且其峰值信噪比达到 28 dB,有效提高了单像素显微成像在高分辨率情况下的成像效率。 |
| 英文摘要: |
| Single pixel imaging is the key technology to solve the problem of imaging in non-visible wavelengths because it only needs a
single point detector without spatial resolution to obtain the spatial information of the target object and reconstruct the image of the object.
The development and application of this technology in high resolution space have the problems of large data collection and slow imaging.
Therefore, this paper designs a Fourier single-pixel microscopy super resolution imaging system to improve the efficiency and quality of
existing single-pixel microscopy imaging. Firstly, a single-pixel microscopic super resolution imaging system was built, and a deep
learning-based super resolution model was introduced to improve its imaging resolution, so as to quickly obtain high-resolution object
reconstruction images. Experimental results show that under the same light intensity signal acquisition time, the imaging resolution can
be improved nearly 9 times, and its peak signal-to-noise ratio reaches 28 dB, which effectively improves the imaging efficiency of single
pixel microscopic imaging under the condition of high resolution. |
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