Fig. 1. Example of the Gaussian fitting and Airy disk corresponding to the point spread function (PSF)^[19]

Fig. 2. Three image resolution calculation methods based on line profile^[21]. (a) Reconstructed super-resolution image of microtubules from U2OS cells. The sub-image on the upper right is an enlargement of the square area in the lower left corner. The intensity distribution of the line markers in this sub-image is displayed above it. The scale bar is 2 μm, and the scale bar of the inset is 100 nm; (b) single-line FWHM resolution of the structure marked by the green line in Fig.2(a); (c) two-point resolution of the structure marked by the blue line in Fig.2(a); (d) projected-line FWHM resolution of the structure marked by the yellow rectangle in Fig.2(a)

Fig. 3. Examples of traditional and super-resolution microscopic images of immunofluorescence labeled microtubules in Drosophila macrophages，the scale bar is 5 μm，and the scale bar of the inset is 0.5 μm^[23]. (a) Wide field image; (b) wide field image after deconvolution; (c) 3D-SIM image; (d) STED image; (e) SMLM image; (f)‒(j) corresponding Fourier spectra

Fig. 4. Resolution evaluation methods for FRC. (a) Workflow used for the determination of the resolution through FRC and corresponding filtering of the image^[24]; (b) correlation between the Fourier transforms of the two independent images over the perimeter of the circle with radius q is calculated resulting in a FRC curve indicating the decay of the correlation with spatial frequency increasing, the scale bar is 1 μm^[27]; (c) illustration for single image FRC^[25]

Fig. 5. Workflow of image decorrelation resolution analysis^[33]. (a) Cross-correlation of the image with its Fourier-filtered normalized version, the scale bar is 5 μm; (b) cross-correlation coefficient as a function of the mask radius; (c) high-pass filtering for the input image; (d) all decorrelation function curves used for the resolution estimation

Fig. 6. Example of the evaluation method based on RSE. (a) Representative workflow for SQUIRREL error mapping^[30]; (b) NanoJ-SQUIRREL for error evaluation. The color block is the corresponding area of the super-resolution image after enlargement and rendering, the scale bar is 5 μm, the scale bar of the region of interest is 1 μm^[39]

Fig. 7. Illustration of two typical types of noise^[44]

Fig. 8. Raw and SIM images under different BSR conditions^[36]

Fig. 9. Two kinds of contrast evaluation methods. (a) Weber contrast values of different samples^[48]; (b) images of fluorescent beads covered with fluorescein in solution outside (left) and inside (right) the structure^[49]; (c) Michelson contrast curve and image display of bright field technology and confocal imaging^[50]

Fig. 10. SSIM computation procedure to quantify the image quality^[52]

Fig. 11. Image of silicon rhodamine (SIR)-DNA-labeled breast cancer cells obtained by spinning disk confocal microscope and the effect of denoising using three different models. Different quantitative evaluation indicators are marked in the figure to evaluate the processing effect^[56]

Fig. 12. Produce of eSRRF image reconstruction^[73]. (a) Raw image, wide field image, and eSRRF image of a microtubule network, the scale bar is 1 μm; (b) eSRRF reconstruction steps; (c) RSP, FRC, and QnR resolution maps with SSIM metric observed over time (from up to bottom); (d) wide field image, eSRRF reconstruction image, low resolution reconstruction image, and low fidelity reconstruction image, the scale bar is 20 μm

Fig. 13. Schematic of autofocusing, slightly modifing the example provided in Ref.[84]

Fig. 14. Super resolution SRN architecture^[96]