Robust online image processing for high-throughput super-resolution localization microscopy

Super-resolution localization microscopy is a powerful tool to visualize molecular structures at a nanoscale resolution. High-density emitter localization combined with a large field of view and fast imaging frame rate is an effective strategy to achieve a high throughput. But the complex algorithms used to precisely localize the overlapping molecules in dense emitter scenarios limits their usage to mostly small image size. Here we present a computationally simple non-iterative method for high-density emitter localization to enable online image processing that remains robust even for low signals and heterogeneous background. Through numerical simulation and biological experiments, we demonstrate that our approach improves the computation speed by two orders of magnitude on CPU and three orders of magnitude upon GPU acceleration to realize online image processing, without compromising localization accuracy for various image characteristics.