Upsampled PSF enables high accuracy 3D superresolution imaging with sparse sampling rate

Single-molecule localization microscopy (SMLM) provides nanoscale imaging, but pixel integration of acquired SMLM images limited the choice of sampling rate, which restricts the information content conveyed within each image. We propose an upsampled point spread function (PSF) inverse modeling method for large-pixel single-molecule localization, enabling precise three-dimensional superresolution imaging with a sparse sampling rate. Our approach could reduce data volume or expand the field of view by nearly an order of magnitude, while maintaining high localization accuracy and greatly improving the imaging throughput with the limited pixels available in existing cameras.