Bayesian photon counting with electron-multiplying charge coupled devices (EMCCDs)

TY - JOUR

T1 - Bayesian photon counting with electron-multiplying charge coupled devices (EMCCDs)

AU - Harpsøe, Kennet Bomann West

AU - Andersen, Michael Ingemann

AU - Rasmussen, Per Kjærgaard

PY - 2012/1/1

Y1 - 2012/1/1

N2 - Context. The EMCCD is a charge coupled devices (CCD) type that delivers fast readout and negligible detector noise, making it an ideal detector for high frame rate applications. Because of the very low detector noise, this detector can potentially count single photons. Aims. Considering that an EMCCD has a limited dynamical range and negligible detector noise, one would typically apply an EMCCD in such a way that multiple images of the same object are available, for instance, in so called lucky imaging. The problem of counting photons can then conveniently be viewed as statistical inference of flux or photon rates, based on a stack of images. Methods. A simple probabilistic model for the output of an EMCCD is developed. Based on this model and the prior knowledge that photons are Poisson distributed, we derive two methods for estimating the most probable flux per pixel, one based on thresholding, and another based on full Bayesian inference. Results. We find that it is indeed possible to derive such expressions, and tests of these methods show that estimating fluxes with only shot noise is possible, up to fluxes of about one photon per pixel per readout.

AB - Context. The EMCCD is a charge coupled devices (CCD) type that delivers fast readout and negligible detector noise, making it an ideal detector for high frame rate applications. Because of the very low detector noise, this detector can potentially count single photons. Aims. Considering that an EMCCD has a limited dynamical range and negligible detector noise, one would typically apply an EMCCD in such a way that multiple images of the same object are available, for instance, in so called lucky imaging. The problem of counting photons can then conveniently be viewed as statistical inference of flux or photon rates, based on a stack of images. Methods. A simple probabilistic model for the output of an EMCCD is developed. Based on this model and the prior knowledge that photons are Poisson distributed, we derive two methods for estimating the most probable flux per pixel, one based on thresholding, and another based on full Bayesian inference. Results. We find that it is indeed possible to derive such expressions, and tests of these methods show that estimating fluxes with only shot noise is possible, up to fluxes of about one photon per pixel per readout.

U2 - 10.1051/0004-6361/201117089

DO - 10.1051/0004-6361/201117089

M3 - Journal article

SN - 0004-6361

VL - 537

JO - Astronomy & Astrophysics

JF - Astronomy & Astrophysics

M1 - A50

ER -