deletions | additions       diff --git a/Results: Centroiding.tex b/Results: Centroiding.tex  index a6e08da..ca0daa0 100644  --- a/Results: Centroiding.tex  +++ b/Results: Centroiding.tex 
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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$13 grid.   From RSI paper:  In our setup with a 100$\times$ objective and no extra magnification in the detection path, each 24$\times$24 μm pixel in the CCD corresponds to 160~nm in the sample plane. This satisfies the  Nyquist sampling limit for 320~nm resolution, a bit above the theoretical resolution limit of $\sim$220~nm for this wavelength and objective. The centroided image shows resolution improvement compared to the sum and brightest pixel images. However, considering the thermal drift associated with the long acquisition time due to the low EBCCD frame rate, the biased distribution of the centroid positions in the horizontal direction, and the many photons required for the centroided image, centroiding with sub-pixel accuracy is of limited benefit in this case. However, for EB-sensors with faster frame rates, centroiding could be used to improve the resolution of the final image.  \textit{Discuss the centroiding results, FPN and bias caused by CCD readout.}