Fast and robust Fourier ptychographic microscopy with position misalignment correction.

Significance: Fourier ptychographic microscopy (FPM) is a new, developing computational imaging technology. It can realize the quantitative phase imaging of a wide field of view and high-resolution (HR) simultaneously by means of multi-angle illumination via a light emitting diode (LED) array, combined with a phase recovery algorithm and the synthetic aperture principle. However, in the FPM reconstruction process, LED position misalignment affects the quality of the reconstructed image, and the reconstruction efficiency of the existing LED position correction algorithms needs to be improved. Aim: This study aims to improve the FPM correction method based on simulated annealing (SA) and proposes a position misalignment correction method (AA-C algorithm) using an improved phase recovery strategy. Approach: The spectrum function update strategy was optimized by adding an adaptive control factor, and the reconstruction efficiency of the algorithm was improved. Results: The experimental results show that the proposed method is effective and robust for position misalignment correction of LED arrays in FPM, and the convergence speed can be improved by 21.2% and 54.9% compared with SC-FPM and PC-FPM, respectively. Conclusions: These results can reduce the requirement of the FPM system for LED array accuracy and improve robustness.

Adaptive correction method of hybrid aberrations in Fourier ptychographic microscopy.

Significance: Fourier ptychographic microscopy (FPM) enables quantitative phase imaging with a large field-of-view and high resolution by acquiring a series of low-resolution intensity images corresponding to different spatial frequencies stitched together in the Fourier domain. However, the presence of various aberrations in an imaging system can significantly degrade the quality of reconstruction results. The imaging performance and efficiency of the existing embedded optical pupil function recovery (EPRY-FPM) aberration correction algorithm are low due to the optimization strategy. Aim: An aberration correction method (AA-P algorithm) based on an improved phase recovery strategy is proposed to improve the reconstruction image quality. Approach: This algorithm uses adaptive modulation factors, which are added while updating iterations to optimize the spectral function and optical pupil function updates of the samples, respectively. The effectiveness of the proposed algorithm is verified through simulations and experiments using an open-source biological sample dataset. Results: Experimental results show that the proposed AA-P algorithm in an optical system with hybrid aberrations, recovered complex amplitude images with clearer contours and higher phase contrast. The image reconstruction quality was improved by 82.6% when compared with the EPRY-FPM algorithm. Conclusions: The proposed AA-P algorithm can reconstruct better results with faster convergence, and the recovered optical pupil function can better characterize the aberration of the imaging system. Thus, our method is expected to reduce the strict requirements of wavefront aberration for the current FPM.

Reduction in required volume of imaging data and image reconstruction time for adaptive-illumination Fourier ptychographic microscopy.

Fourier ptychographic microscopy (FPM) is a promising super-resolution computational imaging technology. It stitches a series of low-resolution (LR) images in the Fourier domain by an iterative method. Thus, it obtains a large field of view and high-resolution quantitative phase images. Owing to its capability to perform high-spatial bandwidth product imaging, FPM is widely used in the reconstruction of conventional static samples. However, the influence of the FPM imaging mechanism limits its application in high-speed dynamic imaging. To solve this problem, an adaptive-illumination FPM scheme using regional energy estimation is proposed. Starting with several captured real LR images, the energy distribution of all LR images is estimated, and select the measurement images with large information to perform FPM reconstruction. Simulation and experimental results show that the method produces efficient imaging performance and reduces the required volume of data to more than 65% while ensuring the quality of FPM reconstruction.

Fast and stable Fourier ptychographic microscopy based on improved phase recovery strategy.

Fourier ptychographic microscopy (FPM) imaging is a computational imaging technology that can reconstruct wide-field high-resolution (HR) images. It uses a series of low-resolution images captured by a camera under different illumination angles. The images are stitched in the Fourier domain to expand their spectral range. Under high-angle illumination, a dark-field image is noisy with a low signal-to-noise ratio, which significantly reduces the reconstruction quality of FPM. Conventional reconstruction algorithms often have low FPM imaging performance and efficiency due to optimization strategies. In response to these problems, this paper proposes an FPM imaging method based on an improved phase recovery strategy to optimize the alternating iterative algorithm. The technique uses an improved threshold method to reduce noise in the image preprocessing stage to maximize the retention of high-frequency sample information. Moreover, an adaptive control factor is added in the subsequent iterative update process to balance the sample spectrum function. This study verifies the effectiveness of the proposed method on both simulation and experimental images. The results show that the proposed method can effectively suppress image background noise and has a faster convergence speed and higher robustness. In addition, it can be used to reconstruct HR complex amplitude images of objects under wide field-of-view conditions.