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

Abstract

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. However, such aberrations are not constrained in existing co-design methods. To solve this problem, we propose the generalized aberration regularization (GAR), which mainly constrains the aberrations that reduce the modulation transfer function (MTF) at the high frequency. Experimental results demonstrate that our approach can significantly improve the quality of high-resolution information in the recovery image compared with the existing co-design methods.