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

基于编码孔径的像差校正方法对光学傅里叶编码和模糊估计得到的像差进行计算像差补偿

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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.

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