Parameter estimation of the structured illumination pattern based on principal component analysis (PCA): PCA-SIM

Abstract

Abstract Principal component analysis (PCA), a common dimensionality reduction method, is introduced into SIM to identify the frequency vectors and pattern phases of the illumination pattern with precise subpixel accuracy, fast speed, and noise-robustness, which is promising for real-time and long-term live-cell imaging.