Volume 42 Issue 1
Feb.  2014
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Zou Pan, Liu Hui, Zhang Wenwen, Chen Qian, Gu Guohua, Zhang Liandong. Parameter estimation of noise distribution model of EMCCD based on the expectation-maximization method[J]. Infrared and Laser Engineering, 2013, 42(1): 268-272.
Citation: Zou Pan, Liu Hui, Zhang Wenwen, Chen Qian, Gu Guohua, Zhang Liandong. Parameter estimation of noise distribution model of EMCCD based on the expectation-maximization method[J]. Infrared and Laser Engineering, 2013, 42(1): 268-272.

Parameter estimation of noise distribution model of EMCCD based on the expectation-maximization method

  • Received Date: 2012-05-22
  • Rev Recd Date: 2012-06-29
  • Publish Date: 2013-01-25
  • Based on the discussion of image noise sources and their statistic characteristics of the electron multiplying CCD(EMCCD), the Poisson-Gaussian-mixture noise distribution model was established. Aiming at the problem that the solution of the maximum likelihood function of the Poisson-Gaussian-mixture distribution model was difficult to solve, the expectation-maximization method was proposed to estimate the parameters of Poisson-Gaussian-mixture noise distribution model of the EMCCD after appropriate initialization settings on the noise model, reducing the complexity of the parameter estimation and achieving equivalent effect of the maximum likelihood estimation. Monte Carlo simulation results and experimental results show that the expectation-maximization method can achieve good performance, provide satisfied fitting features for Poisson-Gaussian-mixture distribution, and obtain high precision parameter estimation values.
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Parameter estimation of noise distribution model of EMCCD based on the expectation-maximization method

  • 1. Science and Technology on Low-light-lever Night Vision Lab,Xi'an 710065,China;
  • 2. Electronic Engineering & Photoelectric Technology College,Nanjing University of Science & Technology,Nanjing 210094,China

Abstract: Based on the discussion of image noise sources and their statistic characteristics of the electron multiplying CCD(EMCCD), the Poisson-Gaussian-mixture noise distribution model was established. Aiming at the problem that the solution of the maximum likelihood function of the Poisson-Gaussian-mixture distribution model was difficult to solve, the expectation-maximization method was proposed to estimate the parameters of Poisson-Gaussian-mixture noise distribution model of the EMCCD after appropriate initialization settings on the noise model, reducing the complexity of the parameter estimation and achieving equivalent effect of the maximum likelihood estimation. Monte Carlo simulation results and experimental results show that the expectation-maximization method can achieve good performance, provide satisfied fitting features for Poisson-Gaussian-mixture distribution, and obtain high precision parameter estimation values.

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