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.

中文翻译：

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基于二分法相关参数估计的快速结构照明显微镜 (dCOR-SIM)

结构照明显微镜（SIM）凭借高光子效率的优势，已发展成为生命科学中研究活细胞动力学最重要的超分辨率成像技术之一。通常，高质量 SIM 超分辨率重建的前提是准确了解照明参数。然而，传统的迭代互相关（COR）方法需要繁琐且耗时的计算才能实现可靠的参数估计，这对复杂场景下的快速动态超分辨率成像提出了巨大的挑战。在这封信中，我们提出了一种基于二分相关参数估计（dCOR-SIM）的高效鲁棒SIM算法，该算法显着消除了传统COR的迭代冗余，从而实现低复杂度的照明参数提取，同时确保精度和抗噪性。实验表明，dCOR-SIM 可以实现高精度参数估计，其效率比传统 COR 高约 10 倍，可在复杂的实验环境中实现快速、高质量的超分辨率重建。我们相信，dCOR-SIM 以其有限的计算负担和对噪声的鲁棒性，将有助于快速、长期的活细胞超分辨率观察。