In these days, the Journal of Light: Science & Applications published a new paper entitled as “Parameter estimation of the structured illumination pattern based on principal component analysis (PCA): PCA-SIM”
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.
Unlike the video-rate immediate graphics processing unit-accelerated open-source reconstruction (VIGOR) method19, which calibrates the illumination parameters in advance, (e.g., by using the COR algorithm, and then reuses these parameters in the subsequent reconstruction). The successful realization of an instant parameter estimating strategy based on PCA demonstrates the feasibility of real-time SIM reconstruction, providing the potential to significantly improve the live-cell imaging performance of SIM under confined imaging conditions with external disturbances. It can be expected that the performance of the proposed scheme can be further promoted, such as the generalization to three dimensional SIM, combination with regularization based deconvolution techniques20, and so on, pushing
its practicability to a higher level.