Photon-limited imaging through scattering medium based on speckle coding

被引:1
|
作者
Han, Jing [1 ]
Miao, Jinye [1 ]
Shi, Yingjie [1 ]
Zhu, Shuo [1 ]
Sun, Yan [1 ]
Bai, Lianfa [1 ]
Guo, Enlai [1 ]
机构
[1] Nanjing Univ Sci & Technol, Jiangsu Key Lab Spectral Imaging & Intelligent Se, Nanjing 210094, Peoples R China
来源
OPTIK | 2022年 / 255卷
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Scattering medium; Photon-limited imaging; Speckle coding; OPTICAL-PHASE CONJUGATION; TURBIDITY SUPPRESSION; TRANSMISSION MATRIX;
D O I
10.1016/j.ijleo.2022.168643
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Photon-limited imaging a target hidden behind a scattering medium is a hot technology at present, and it has important applications in many fields. A basic problem is that the target information is annihilated by noise from the speckle captured under weak illumination conditions, which makes it difficult to reconstruct the target. In order to solve this problem, we propose a highly sensitive approach to image through scattering media based on encoding speckles. Under a light level of 0.1 Lux, the target passing through the scattering medium is encoded multiple times by the Gaussian matrix, which can better extract the effective information in speckles. Theoretically, increasing the number of encoding times can improve the ability of information extraction, but also cause time consuming. But our method only needs to encode 39.1% of the full sampling to recover the original target, which effectively improves the encoding efficiency. In addition, Our algorithm has perfect noise resistance, when artificial noise is added to the data , the average peak signal to noise ratio (PSNR) of the algorithm can get 18.16 dB, and the average structural similarity index measure (SSIM) reaches more than 0.65. We also experimentally verify the effects of the algorithm with different network parameters on target reconstruction. The strong reconstruction ability of the proposed method in a low illumination environment can provide a basis for practical application of the proposed method.
引用
收藏
页数:11
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