Yeh Li-Hao, Tian Lei, Waller Laura
Electrical Engineering and Computer Sciences, University of California at Berkeley, Berkeley, CA 94720, USA.
Electrical Engineering and Computer Sciences, University of California at Berkeley, Berkeley, CA 94720, USA; Electrical & Computer Engineering, Boston University, Boston, MA 02215, USA.
Biomed Opt Express. 2017 Jan 9;8(2):695-711. doi: 10.1364/BOE.8.000695. eCollection 2017 Feb 1.
Structured illumination microscopy (SIM) improves resolution by down-modulating high-frequency information of an object to fit within the passband of the optical system. Generally, the reconstruction process requires prior knowledge of the illumination patterns, which implies a well-calibrated and aberration-free system. Here, we propose a new strategy for SIM that does not need to know the exact patterns , but only their covariance. The algorithm, termed PE-SIMS, includes a pattern-estimation (PE) step requiring the uniformity of the sum of the illumination patterns and a SIM reconstruction procedure using a statistical prior (SIMS). Additionally, we perform a pixel reassignment process (SIMS-PR) to enhance the reconstruction quality. We achieve 2× better resolution than a conventional widefield microscope, while remaining insensitive to aberration-induced pattern distortion and robust against parameter tuning.
结构照明显微镜（SIM）通过下调物体的高频信息以使其适合光学系统的通带，从而提高分辨率。通常，重建过程需要对照明图案有先验知识，这意味着需要一个校准良好且无像差的系统。在此，我们提出一种新的SIM策略，该策略无需知道确切的图案，而仅需知道它们的协方差。该算法称为PE-SIMS，包括一个需要照明图案总和均匀性的图案估计（PE）步骤以及一个使用统计先验的SIM重建过程（SIMS）。此外，我们执行像素重新分配过程（SIMS-PR）以提高重建质量。我们实现了比传统宽场显微镜高2倍的分辨率，同时对像差引起的图案失真不敏感，并且对参数调整具有鲁棒性。
