Super-resolution reconstruction for extremely low-light imaging by using intensified CCD or CMOS camera

被引:0
|
作者
Zhao Hui [1 ]
Fan Xuewu [1 ]
Yang Mingyang [1 ]
Pan Yue [1 ]
Li Baopeng [1 ]
Zhang Minrui [1 ]
机构
[1] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Space Opt Lab, Xian 710019, Peoples R China
来源
OPTOELECTRONIC IMAGING AND MULTIMEDIA TECHNOLOGY IX | 2022年 / 12317卷
关键词
low-light imaging; super-resolution; ICCD; ICMOS; RESOLUTION;
D O I
10.1117/12.2641587
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
It is difficult for normal CCD or CMOS camera to obtain high quality images under extremely low-light conditions for example the new moon or the quarter moon because the photons arriving at the detector are so few that signal to noise ratio (SNR) is much lower than what is necessary to resolve finer details in the nighttime scenario. To solve this problem, the intensified CCD or CMOS camera is adopted and the few photons is amplified to improve the SNR a lot. However, the intensifier is mainly composed of the cathode, MCP (Micro-channel-plate) and fluorescent screen and this complex structure and the multiple photoelectric conversion during the photon amplification process will lead to a big equivalent pitch size, which degrades the spatial resolution. Therefore in this manuscript, by improving the classical iterative back projection (IBP) algorithm a super-resolution reconstruction algorithm is proposed. By fusing multiple quite noisy low-light images having sub-pixel displacements between each other, both the spatial resolution and the SNR could be enhanced. In the in-lab experiments, the spatial resolution can be increased to nearly 1.8 times the original one. Besides that, the increment in SNR bigger than 6dB and 9dB could be obtained for the quarter moon and the new moon light condition respectively. The out-door experiments show the similar results and besides that by fusing sub-pixel shifted low-light images corresponding to different low-light conditions together, the reconstructed high-resolution images will have even better visual performance.
引用
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页数:11
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