deletions | additions       diff --git a/Results: Centroiding.tex b/Results: Centroiding.tex  index 682ff2d..f0ace9e 100644  --- a/Results: Centroiding.tex  +++ b/Results: Centroiding.tex 
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where $N_{max}$, $N_{min}$, and $N_{mean}$ are the maximum, minimum and average number of counts in the 5$\times$5 array of subpixel positions, respectively. For a completely random distribution, this number should approach zero with increasing number of photons.  Several of ThunderSTORM's centroiding algorithms were tested to find an algorithm that leads to a minimum amount of fixed pattern noise. The distributions of centroided positions are shown in  Fig~\ref{fig_pixelimages}, where the pixels are further divided into a 13$\times$13 grid. The results are summarised in Table~\ref{table:results}. Maximum likelihood (ML) fitting with a Gaussian PSF produces the most uniform distribution of localised positions (Fig~\ref{fig_pixelimages}a)  with FPN of 71\%. 71\%, as well as the finding the highest number of photons.  As reported previously,\cite{Hirvonen2014_rsi} the horizontal widening of the photon events, most likely caused by the CCD read-out, causes a bias in the centroided positions and photons are most likely to be found towards the right edge of the pixel. Radial symmetry method produces similar  results with a slightly higher FPN of 91\%, but causes changes the  bias in to  the vertical direction. direction (Fig~\ref{fig_pixelimages}b). Other methods produce results that are similar to the ML, but with higher FPN and lower photon count, an example of weighted LS fit with integrated Gaussian PSF is shown in Fig~\ref{fig_pixelimages}c.