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基于EMCCD 的光子计数成像方法与实验
引用本文:张磊,石峰,邹燕,张龙,何伟基,程宏昌,顾国华,陈钱.基于EMCCD 的光子计数成像方法与实验[J].红外与激光工程,2015,44(1):384-390.
作者姓名:张磊  石峰  邹燕  张龙  何伟基  程宏昌  顾国华  陈钱
作者单位:1.江苏省光谱成像与智能感知重点实验室南京理工大学,江苏南京210094;
基金项目:微光夜视技术重点实验室开放基金(J110508;J20130501);国家自然科学基金
摘    要:讨论了在复杂背景条件下采用EMCCD 实现光子计数成像的处理策略,提出了一种双重阈值滤波方法并通过实验验证了其有效性。根据EMCCD 的成像模型,将EMCCD 的输出图像表示为光子事件、偏置噪声和伪光子噪声事件的集合。通过采集多幅EMCCD 的输出图像,将光子事件检测问题转化为标准的二元假设检测问题。利用贝叶斯判决,可以得到光子事件检测的最佳检测法则,使光子事件的误判代价达到最小,从而检测出光子事件及其空间分布特征。通过实验对比可以发现:提出的方法明显优于普通的累加积分方法,适合生物微光检测等超低照度条件下的成像领域。

关 键 词:电子倍增CCD    光子计数成像    双重阈值滤波    微弱光检测
收稿时间:2014-05-11

Method and experiment of photon counting imaging based on EMCCD
Zhang Lei,Shi Feng,Zou Yan,Zhang Long,He Weiji,Cheng Hongchang,Gu Guohua,Chen Qian.Method and experiment of photon counting imaging based on EMCCD[J].Infrared and Laser Engineering,2015,44(1):384-390.
Authors:Zhang Lei  Shi Feng  Zou Yan  Zhang Long  He Weiji  Cheng Hongchang  Gu Guohua  Chen Qian
Affiliation:1.Jiangsu Key Lab of SIIS,Nanjing University of Science & Technology,Nanjing 210094,China;2.Science and Technology on LLL Night Vision Lab,Xi'an 710065,China;3.Nanjing Military Representation Bureau,Nanjing 210024,China
Abstract:In this paper, a double-threshold filter strategy was proposed and experimentally tested to improve the accuracy of photon counting imaging with an electron multiplying charge-coupled device, by taking into account the addition bias noise and Pseudo-photon noise during photon counting mode. Photon counting event detection was achieved by using amplitude threshold and frequency threshold filter to eliminate the bias noise and Pseudo-photon noise. Based on Bayesian estimation on multi-imaging, an optimal detection rule was found with minimum error cost. Experiment indicates that double-threshold filter strategy improves the photon detection accuracy than usual integrate method, and is suitable for imaging in ultra-low-light conditions such as biological dim light detection.
Keywords:electron multiplying charge-coupled device  photon counting imaging  double-threshold filter  low light level detection
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