Fast-Structured Illumination Microscopy Based on Dichotomy–Correlation Parameter Estimation (dCOR-SIM)
Jiaming Qian, Kailong Xu, Shijie Feng, Yongtao Liu, Haigang Ma, Qian Chen, Chao Zuo
Abstract
Structured illumination microscopy (SIM) has developed into one of the most significant super-resolution imaging techniques for studying the dynamics of live cells in the life sciences, thanks to the advantage of high photon efficiency. Usually, high-quality SIM super-resolution reconstruction presupposes accurate knowledge of the illumination parameters. However, the conventional iterative cross-correlation (COR) method requires cumbersome and time-consuming computations to realize reliable parameter estimation, posing a great challenge for fast, dynamic super-resolution imaging in complex scenes. In this letter, we propose an efficient and robust SIM algorithm based on dichotomy–correlation parameter estimation (dCOR-SIM), which significantly eliminates the iteration redundancy of conventional COR to enable low-complexity illumination parameter extraction while ensuring precision and noise immunity. Experiments demonstrate that dCOR-SIM can achieve high-accuracy parameter estimation with an efficiency ∼10 times better than conventional COR for fast, high-quality super-resolution reconstruction in complex experimental environments. We believe that dCOR-SIM, with its limited computational burden and robustness to noise, will facilitate fast, long-term live-cell super-resolution observations.