Inverse Matrix Based Phase Estimation Algorithm For Structured Illumination Microscopy

The fast imaging speed and low-intensity requirement of structured illumination microscopy (SIM) have made it one of the most widely used imaging tools in live cell imaging. In order to obtain a high fidelity reconstructed image, a precise estimation of the phase of the illumination pattern is required, especially in those structured illumination based techniques that rely on high-order harmonics to improve the resolution. This can be achieved in one of two fundamental ways. The first is to build a high-end control system capable of shifting a sinusoidal pattern with high precision, while the second is to apply estimation algorithms to determine how patterns shift during post-processing. The latter method is preferred in low-cost super-resolution imaging systems; however, existing algorithms are either time-consuming or fail due to noise and a low modulation depth. In this paper, we introduce additional matrixes into the phase estimation algorithm and propose an inverse matrix based phase estimation method with which analytical solutions of the phases can be determined without iteration. The proposed algorithm was validated via simulation and experiments using a home-made total internal reflection fluorescent SIM system (TIRF-SIM). When tested, the method obtained the true phase even when the modulation depth was low. The source code is now available for download by researchers and others. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement