Computational aberration compensation by coded-aperture-based correction of aberration obtained from optical Fourier coding and blur estimation.

Abstract

We report a novel generalized optical measurement system and computational approach to determine and correct aberrations in optical systems. The system consists of a computational imaging method capable of reconstructing an optical system's pupil function by adapting overlapped Fourier coding to an incoherent imaging modality. It recovers the high-resolution image latent in an aberrated image via deconvolution. The 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 overlapped Fourier coding and blur estimation (CACAO-FB). It is well-suited for various imaging scenarios where aberration is present and where providing a spatially coherent illumination is very challenging or impossible. We report the demonstration of CACAO-FB 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-FB ultimately allows for an aberrated imaging system to achieve diffraction-limited performance over a wide field of view by casting optical design complexity to computational algorithms in post-processing.