Simulating Multi-Colour Single-Molecule Localisation Microscopy Using an RGB Camera

Abstract

High-order multiplexing in single-molecule localisation microscopy (SMLM) is limited by trade-offs between spectral discrimination, imaging speed, and experimental complexity. Here, we show that RGB cameras provide a simple and scalable solution for multi-colour SMLM by exploiting their intrinsic spectral sensitivity for statistical fluorophore discrimination. Using a realistic simulation framework incorporating experimentally derived photon budgets, optical response functions, and camera noise, we achieve simultaneous classification of up to six fluorophores with a mean precision of [~]98%, including perfect discrimination of spectrally overlapping dye pairs, while maintaining an average localisation precision of [~]3.2 nm. Performance remains robust to variations in classification thresholds but degrades with increasing fluorophore number and reduced photon budgets due to spectral overlap and photon noise. These results establish RGB detection as a cost-effective and experimentally straightforward alternative to conventional spectral imaging approaches, enabling accessible, high-throughput multiplexed super-resolution imaging.