Adaptive denoising method based on iterative process for Fourier ptychographic microscopy

摘要

Fourier ptychographic microscopy (FPM) is a wide-field and high-resolution (HR) imaging technique, reconstructing HR spectrum from a series of low-resolution (LR) images captured at different illumination angles. In FPM, the quality of captured images is a critical factor that affects the final reconstruction HR result, so an effective denoising method is an indispensable process step. Here we propose an adaptive denoising method for FPM, which takes advantage of the data redundancy of FPM to separate signal from noise without any pre-knowledge about the noise statistics. Different from the traditional denoising method by reducing a fixed threshold, the proposed adaptive denoising method can more effectively eliminate noise and preserve more effective signals. This paper explains adaptive denoising principle and process steps, and finally demonstrates that this method not only improve the accuracy and robustness of FPM. but also relax the imaging performance requirement for implementing high-quality FPM reconstruction.