摘要
在去除光子图像的本底噪声时,根据微弱点目标的探测统计特性,以泊松分布均值与方差相等的特点为判据,提出了一种确定阈值选取范围的新方法。利用点过程的分析方法研究了光子受限点目标的探测统计特性,并进行了实验研究,结果表明光子受限点目标的探测统计特性服从平稳泊松点过程。利用以上分析方法可以快速地获得微弱点目标事件的期望发生率,以及在下一段时间内目标至少再出现一次的概率,从而为后续的目标探测、跟踪以及位置预测奠定了基础。
A novel method of choosing threshold range,which bases on the criterion that the mean value and the variance are equal in Poisson distribution,is proposed to eliminate the background noise in photon images.Point process analysis method is used to study the statistical properties of point target under the photon limited condition and verify the results experimentally.The results show that the detection statistics of point target under the photon limited condition subject to a stationary Poisson point process.Through the point process analysis method,the expectation occurrence-rate of ultra-weak target and the recurrence probability in the follow period can be obtained quickly,which lay the foundations for detection,tracking and location forecasting.
出处
《光学技术》
CAS
CSCD
北大核心
2012年第3期340-344,共5页
Optical Technique
关键词
光子成像
泊松分布
泊松点过程
photon imaging
Poisson distribution
Poisson point process
