Fourier ptychographic microscopy using a generalized Anscombe transform approximation of the mixed Poisson-Gaussian...

Area of Science:

• Microscopy
• Computational Imaging
• Optics

Background:

• Fourier ptychographic microscopy (FPM) combines synthetic aperture and phase retrieval to achieve wide field-of-view and high-resolution imaging.
• FPM reconstruction is susceptible to various noise types, including Gaussian, Poisson, and mixed Poisson-Gaussian noise, impacting image quality.

Purpose of the Study:

• To develop a novel and efficient noise reduction method for Fourier ptychographic microscopy reconstruction.
• To improve the robustness and performance of FPM in the presence of various noise sources.

Main Methods:

• Introduced a generalized Anscombe transform approximation (GAT) for noise modeling in FPM.
• Employed maximum likelihood theory to formulate the FPM optimization problem within the GAT framework.
• Developed the generalized Anscombe transform approximation Fourier ptychographic (GATFP) reconstruction method.

Main Results:

• The GATFP reconstruction method demonstrated superior performance in handling noise compared to existing approaches.
• Validation using simulated and real experimental data confirmed the effectiveness of the proposed method.
• Achieved state-of-the-art results in FPM image reconstruction with noise reduction.

Conclusions:

• The GATFP reconstruction method offers an effective solution for noise reduction in Fourier ptychographic microscopy.
• This approach enhances the reliability and quality of FPM reconstructions, particularly in noisy conditions.