Inverse synthetic aperture Fourier ptychography.

Area of Science:

• Optical imaging
• Computational imaging
• Microscopy

Background:

• Fourier ptychography (FP) reconstructs high-resolution images from low-resolution measurements.
• Traditional FP methods require complex setups with changing illumination or camera positions.
• These conventional approaches increase cost and complexity in optical imaging systems.

Purpose of the Study:

• To introduce a novel Fourier ptychography approach using sample tilt for measurement diversity.
• To develop a learning-based method for estimating sample orientation from intensity measurements.
• To enable synthetic aperture imaging without prior knowledge of the tilt angle.

Main Methods:

• Developed inverse synthetic aperture Fourier ptychography (ISAFP) by utilizing sample tilt for measurement diversity.
• Introduced a novel learning-based algorithm to estimate sample orientation from dual plane intensity data.
• Experimentally validated the ISAFP method through simulations and tabletop optical experiments.

Main Results:

• Demonstrated that sample tilt can effectively generate measurement diversity in FP.
• Successfully reconstructed high-resolution images using ISAFP without explicit tilt angle information.
• Validated the robustness and feasibility of the proposed learning-based orientation estimation.

Conclusions:

• ISAFP offers a simplified and cost-effective alternative to traditional FP acquisition methods.
• The learning-based orientation estimation is crucial for enabling FP without explicit tilt angle knowledge.
• This work advances synthetic aperture imaging techniques for broader applications in microscopy and optical sciences.