Estimation of the Probability Density Function of Random Displacements from Images

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We introduce a novel approach to Image-based Probability Estimation of Displacement (iPED) which is direct estimation of the PDF of displacement of racers within images. Data sets to reproduce the plots and sample images are available here.

Version 1.0 - published on 27 Jul 2020 doi:10.4231/34TJ-S109 - cite this Archived on 27 Aug 2020

Licensed under CC0 1.0 Universal

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This is the data sets that used to develop, verify, and demonstrate the use of Image-based Probability Estimation of Displacement (iPED). iPED is an image-based algorithm to find the probability density function (PDF) of particle displacements from a sequence of images. iPED does not make any assumptions about the shape of the particle intensity profile or the PDF of the displacements. We compare iPED’s performance with the previous correlation-based method for both Gaussian and non-Gaussian particle intensity profiles undergoing Gaussian or non-Gaussian processes. The datasets present here can be used to reproduce the figures and analysis reported in the paper.

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