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  %\subsection{Data processing}  The frames containing single photon events were processed with ThunderSTORM \cite{Ovesny2014} superresolution imaging plug-in for ImageJ. Due to memory limitations, the USAF test chart  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 an approximate localisation algorithm locates the center pixel of each event. A sub-pixel localisation algorithm then calculates the center of the events 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 localisation 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 test chart  data, and a PIT of 1.5*std(Wave.F1) for cell data, with the watershed algorithm enabled for all data. All sub-pixel localisation methods offered by ThunderSTORM (Maximum Likelihood (ML) and Least squares (LS) fitting with both Gaussian (G) and Integrated Gaussian (IG) point-spread function (PSF), Centroid of local neighborhood, Radial Symmetry) were tested, with fitting parameters optimised for maximum photon count and minimum likelihood of false photon event recognition.