压缩传感用于极弱光计数成像
Compressed sensing for ultra-weak light counting imaging
查看参考文献33篇
文摘
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为解决灵敏度达到单光子水平的面阵探测器件其单位像素上灵敏度有限和测量数多等问题,研制了具有极高灵敏度的成像系统来实现欠采样的极弱光成像探测。该成像系统基于光子计数成像技术和压缩感知理论,利用数字微镜器件(DMD)完成随机空间光调制,通过单光子点探测器收集光子,以计数形式记录下光强值。然后,利用算法重建出极弱光照明下的图像。文中设计了相关实验,研究了测量数、光强极弱程度和测量时间对成像质量的影响。最后,引入了图像质量评价标准和系统信噪比,分析对比了实验数据。结果表明,当测量数高于信号总维度的19.5%时,系统能完美成像,信噪比可低至2. 843 8 dB,DMD单位像素上的平均光子数可低于1.106 count/s,成像的关键在于信号的波动大于噪声的波动。该成像系统基本满足了极弱光成像探测在光强、灵敏度和采样数等方面的要求。 |
其他语种文摘
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Since array detectors with sensitivity to single photon level were limited by sensitivity on each pixel and needed large number of measurements, an imaging system with high sensitivity was designed to realize under-sampling ultra-weak light imaging detection. This imaging system based on photon counting technique and compressed sensing theory employed a Digital Micromirror Device(DMD) to complete the random spatial light modulation, and used a single photon point detector to collect photons. The total light intensity was recorded by the form of photon counting. Then, the image of an object under ultra-weak light illumination could be reconstructed by an algorithm. The influences of the number of measurements, ultra-weak light intensity level and measurement time on the quality of imaging were investigated by experiments. Furthermore, the evaluation criterion of reconstructed image and the Signal to Noise Ratio (SNR) of the system were discussed to analyze the experimental data. The experimental results show that when the number of measurements is greater than19.5 percent of the dimension of data, it can acquire a good reconstruction, the SNR of the system can be even decreased to 2. 843 8 dB, and the average count of photons on each pixel of the DMD can be lower than 1. 106 count/s. Experiments also prove that the key of imaging lies in the fact that the fluctuation of signal should be greater than the fluctuation of noise. It concludes that this imaging system meets the demand of ultra-weak light imaging detection for ultra-weak light intensity, high sensitivity and few measurements. |
来源
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光学精密工程
,2012,20(10):2283-2292 【核心库】
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DOI
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10.3788/ope.20122010.2283
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关键词
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光子计数成像
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压缩传感
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极弱光
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成像系统
;
雪崩二极管
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地址
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1.
中国科学院空间科学与应用研究中心空间科学实验技术研究室, 北京, 100190
2.
北京理工大学物理学院, 北京, 100081
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语种
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中文 |
ISSN
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1004-924X |
学科
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机械、仪表工业;自动化技术、计算机技术 |
基金
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国家863计划
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文献收藏号
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CSCD:4685604
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参考文献 共
33
共2页
|
1.
Raptor Photonics.
The ultimate in low light sensitivity,2012
|
被引
1
次
|
|
|
|
2.
Id Quantique.
ID100 single-photon counting detector datasheet,2011
|
被引
1
次
|
|
|
|
3.
Micro Photon Devices.
MPD's single-photon detection modules datasheet,2011
|
被引
1
次
|
|
|
|
4.
杜克铭. 基于压缩传感的光子计数成像系统.
红外与激光工程,2012,41(2):363-368
|
被引
6
次
|
|
|
|
5.
尼启良. 使用感应电荷位敏阳极的极紫外单光子计数成像系统.
光学精密工程,2010,18(12):2543-2548
|
被引
14
次
|
|
|
|
6.
何玲平. 楔条形阳极光子计数探测器成像性能的检测.
光学精密工程,2009,17(11):2699-2704
|
被引
11
次
|
|
|
|
7.
崔东旭. 光子计数法测量类针孔成像光斑照度.
光学精密工程,2012,20(4):733-738
|
被引
2
次
|
|
|
|
8.
Shapiro J H. Computational ghost imaging.
Phy. Rev. A,2008,78:061802(R)
|
被引
180
次
|
|
|
|
9.
Katz O. Compressive ghost imaging.
Appl. Phys. Lett,2009,95:131110
|
被引
119
次
|
|
|
|
10.
Kocsis S. Observing the average trajectories of single photons in a two-slit interferometer.
Sci,2011,332:1170-1173
|
被引
18
次
|
|
|
|
11.
Zhang D. Correlated two-photon imaging with true thermal light.
Opt. Lett,2005,30:2354-2356
|
被引
99
次
|
|
|
|
12.
Pittman T. Optical imaging by means of two-photon quantum entanglement.
Phys. Rev. A,1995,52(5):R3429-R3432
|
被引
248
次
|
|
|
|
13.
Bennink R. Quantum and classical coincidence imaging.
Phys. Rev. Lett,2004,92(3):0336011-0336014
|
被引
52
次
|
|
|
|
14.
Albota M. Three-dimensional imaging laser radar with a photoncounting avalanche photodiode array and microchip laser.
App. Opt,2002,41(36):7671-7678
|
被引
30
次
|
|
|
|
15.
Howland G A. Photon-counting compressive sensing laser radar for 3D imaging.
Appl. Opt,2011,50(31):5917-5920
|
被引
20
次
|
|
|
|
16.
Donoho D L. Compressed sensing.
IEEE Trans. Inform. Theory,2006,52(4):1289-1306
|
被引
2901
次
|
|
|
|
17.
Cand Es E J. Compressive sampling.
Proc. Int. Cong. Mathematicians,2006:1433-1452
|
被引
1
次
|
|
|
|
18.
Baraniuk R G. Compressive sensing.
IEEE Signal Process. Mag,2007,24(4):118-121
|
被引
503
次
|
|
|
|
19.
Candes E J. Robust uncertainty principles:Exact signal reconstruction from highly incomplete frequency information.
IEEE Trans. Inform. Theory,2006,52(2):489-509
|
被引
1352
次
|
|
|
|
20.
Studer V. Compressive fluorescence microscopy for biological and hyperspectral imaging.
Proceedings of the National Academy of Sciences,2012:E1679-E1687
|
被引
22
次
|
|
|
|
|