Localization-based super-resolution microscopy with an sCMOS camera part III: camera embedded data processing significantly reduces the challenges of massive data handling

Abstract

We present a camera embedded data processing method for localization microscopy (LM) with faster detectors such as scientific complementary metal-oxide semiconductor (sCMOS) cameras. Based on the natural sparsity of single molecule images, this method utilizes the field programmable gate array chip inside a camera to identify and export only the regions containing active molecules instead of raw data. Through numerical simulation and experimental analysis, we found that this method can greatly reduce data volume (<10%) with negligible loss of useful information (<0.2%) at molecular densities <0.2 molecules/μm(2), thus significantly reducing the challenges of data transfer, storage, and analysis in LM.