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  %\subsection{Data processing}  The frames containing single photon events were processed with the ThunderSTORM \cite{Ovesny2014} superresolution imaging plug-in for ImageJ. Due to memory limitations, the USAF data was processed in 6$\times$5,000 and the cell data in 3$\times$2,000 image stacks. The frames containing single photon events were processed with the ThunderSTORM \cite{Ovesny2014} superresolution imaging plug-in for ImageJ. Due to memory limitations, the USAF data was processed in 6$\times$5,000 and the cell data in 3$\times$2,000 image stacks. The  software first detects the events from the noise background, and due to the peaked pulseheight distribution of the photon events \cite{Hirvonen2014_rsi} the setting of a threshold is relatively straight-forward. An an  approximate localization algorithm locates the center pixel of each event, and a event. A  sub-pixel localization algorithm then calculates the center of the events within the pixel. with greater resolution.  The software camera parameters were set to 80.0~nm pixel size and 36 photoelectrons per A/D count. The base level varied between image stacks due to fluctuations in the EBCCD temperature, and was set to the average minimum grey value for the image stack in the range of 100-140 A/D counts. A wavelet (b-spline) image filter was applied with order of 3 and scale of 2.0. For the approximate localization of the events, the centroid of connected components method was used with a peak intensity threshold (PIT) of 2*std(Wave.F1) for the USAF data, and a PIT of 1.5*std(Wave.F1) for cell data, with the watershed algorithm enabled for all data.