Generalized aberration regularization in the single-lens computational imaging system design.

The restoration algorithm can reduce the aberration blur in the single-lens computational imaging system. The single lens and the restoration algorithm should be co-designed to improve the imaging performance of the whole computational imaging system. By investigating the influence of aberrations on computational imaging quality, we find there are aberrations that cannot be removed by restoration algorithm, which cause the loss of high-resolution information.

End-to-end learned single lens design using improved Wiener deconvolution.

End-to-end single-lens imaging system design is a method to optimize both optical system and reconstruction algorithm. Most end-to-end single lens systems use convolutional neural networks (CNN) for image restoration, which fit the transformation relationship between the aberrated image and the ground truth image in the training set. Based on the principle of optical imaging, we realize non-blind image restoration through Wiener deconvolution.