Computational optical imaging with a photonic lantern

Area of Science:

• Biomedical Optics
• Optical Engineering
• Computational Imaging

Background:

• Optical fibers are ideal for in-vivo biological imaging due to their flexibility.
• Current microendoscopic techniques face limitations in achieving high spatial resolution.
• Need for advanced imaging modalities to overcome resolution barriers in biological studies.

Purpose of the Study:

• To develop a high-resolution microendoscopy technique using multicore fibers (MCF).
• To demonstrate a novel single-pixel imaging approach for in-vivo biological visualization.
• To introduce a computational imaging algorithm for reconstructing images from MCF-based data.

Main Methods:

• Utilized a multicore fiber (MCF) with a tapered photonic lantern transition at the distal end.
• Individually excited single-mode MCF cores to project distinct, stable multimode light patterns.
• Employed a single-pixel detector to measure transmitted light fractions for each pattern.
• Developed and applied the SARA-COIL computational imaging algorithm for image reconstruction.

Main Results:

• Demonstrated stable projection of distinct multimode light patterns from the photonic lantern.
• Successfully implemented single-pixel imaging by measuring transmitted light through an object.
• Reconstructed object images using the SARA-COIL algorithm and pre-measured light patterns.
• Achieved high-resolution microendoscopy, overcoming limitations of current methods.

Conclusions:

• The developed MCF-based photonic lantern system offers a route to high-resolution microendoscopy.
• Single-pixel imaging combined with computational reconstruction provides a viable method for in-vivo biological imaging.
• This technology has the potential to significantly advance the visualization of biological processes.