Computational aberration compensation by coded aperture-based correction of aberration obtained from Fourier ptychography (CACAO-FP)

TL;DR

This paper introduces CACAO-FP, a computational imaging method that corrects optical aberrations using Fourier ptychography and coded apertures, enabling high-resolution imaging with simple, aberration-prone lenses.

Contribution

The paper presents a novel computational approach combining Fourier ptychography and coded apertures for aberration correction without requiring spatial coherence.

Findings

Successfully corrected aberrations in retinal imaging of a rhesus macaque.

Achieved diffraction-limited resolution with a simple lens.

Demonstrated robustness to noise in aberration correction.

Abstract

We report a novel generalized optical measurement system and computational approach to determine and correct aberrations in optical systems. We developed a computational imaging method capable of reconstructing an optical system's aberration by harnessing Fourier ptychography (FP) with no spatial coherence requirement. It can then recover the high resolution image latent in the aberrated image via deconvolution. Deconvolution is made robust to noise by using coded apertures to capture images. We term this method: coded aperture-based correction of aberration obtained from Fourier ptychography (CACAO-FP). It is well-suited for various imaging scenarios with the presence of aberration where providing a spatially coherent illumination is very challenging or impossible. We report the demonstration of CACAO-FP with a variety of samples including an in-vivo imaging experiment on the eye of a rhesus macaque to correct for its inherent aberration in the rendered retinal images. CACAO-FP ultimately allows for a poorly designed imaging lens to achieve diffraction-limited performance over a wide field of view by converting optical design complexity to computational algorithms in post-processing.