Dataset DOI: 10.5061/dryad.f7m0cfzbr

Description of the data and file structure

Files contain data used to plot the figures in the manuscript "Super-Resolution Imaging via Photon Enumeration". Details describing the data can be found in the manuscript.

Files and variables

Files in FigData.zip:

Fig1columnPND.mat

Photon Number Distributions (probability as a function of number of detected photons)  measured in a single column of pixels and shown in Fig. 1 as an example.

Fig2a3Ddata.mat

Photon Number Distributions (probability as a function of number of detected photons) measured for 3 thermal sources for 128 x 128 pixels of the PNR camera.

Fig2aIntMap.mat

Intensity map (mean number of photons measured in each pixel) calculated from the PNR data Fig2a3Ddata.mat and shown in Fig. 5(a) of the revised manuscript.

Fig2b.mat, Fig2c.mat, Fig2d.mat, Fig2e.mat

Photon Number Distributions (probability as a function of number of detected photons) measured for 3 thermal sources and plotted in Figs. 5 (b)-(e). Each file contains a PND for the pixel marked in Fig. 5(a) of the manuscript.

Fig3a.mat

Single-parameter estimation (RMSE of distance between two sources $\delta_x$ with known photon fluxes and known centroid normalized by point spread function (PSF) width) for the distance between two sources set to zero ($\delta_x=0$). 4 cases: balanced S-RIPE, balanced DI, unbalanced S-RIPE, unbalanced DI.

Fig3b.mat

Multi-parameter estimation (RMSE of positions of both sources $\{x_1,x_2\}$ and both photon fluxes $\{\mu_1,\mu_2\}$, $\mu_1\neq\mu_2$, for zero and non-zero separation of the sources normalized by PSF width). In the case of zero separation, DI fails to converge because in the case of zero separation, there is no difference between intensity distributions produced by a single source (i.e.\ $\mu_1 = 0$ or $\mu_2 = 0$) and a pair of sources with any arbitrary photon flux such that the total photon flux is equal to the photon flux of the single light source, while S-RIPE demonstrates performance similar to the single-parameter problem. In the case of non-zero separation, both methods demonstrate near-optimal scaling.

Fig4b.mat

Root mean square error (RMSE) of the S-RIPE technique applied to the experimental data for five thermal sources normalized by PSF width in comparison to simulations for S-RIPE and direct imaging as a function of the separation between the sources normalized by PSF width.

Fig5aIntMap.mat

Raw measured intensity distribution (mean number of photons measured in each pixel) for five thermal sources separated by $\delta_x<\sigma_\text{PSF}$.

Fig5bIntMap.mat

The intensity distribution (mean number of photons measured in each pixel) where raw data from Fig5aIntMap.mat was binned and averaged in 8x8 pixel groups

Fig5c.mat

Positions (pixel coordinates) and intensities (mean number of photons) of the sources extracted with S-RIPE from the raw data

Fig5d.mat

Positions (pixel coordinates) and intensities (mean number of photons) of the sources extracted with S-RIPE from the 8x8 binned data

Fig5groundTruth.mat

Ground truth location (pixel coordinates) of the sources.

Code/software

MATLAB or any other software that can read .mat files.