Autocorrelation central value in clipped photon-counting detection from the moments of the total number of counts

Mathematics – Probability

Scientific paper

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Astronomy, Autocorrelation, Counting, Detection, Faint Objects, Image Processing, Photons, Analysis Of Variance, Computerized Simulation, Pixels, Probability Density Functions

Scientific paper

Many existing photon-limited image detectors are not able to distinguish whether a photo-event in one pixel comes from single or multiple events, and the output of such devices consists only a series of binary values denoting presence or absence of counts in each pixel. The counts are therefore clipped, and this leads to a hole in the Autocorrelation estimate that must be removed for image recovery applications. In this letter, two methods to obtain the Autocorrelation central value from clipped photon-counting data are presented. They are based on the statistical analysis of the total number of counts in one frame. One of the methods requires a smaller number of frames to provide good statistical accuracy while the other has a wider intensity range of applicability.

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