Revealing the preference for correcting separated aberrations in joint optic-image design

TL;DR

This paper introduces a novel approach for joint optical and algorithmic design by characterizing separated aberrations, proposing a correction network, and demonstrating significant improvements in mobile lens design and computational photography.

Contribution

It presents a new optical characterization method, an aberration correction network, and insights into aberration correction preferences for efficient joint design.

Findings

Preference order for aberration correction: longitudinal chromatic, lateral chromatic, spherical, field curvature, coma, astigmatism.

Achieved 10% reduction in mobile phone lens module length.

Enhanced computational photography quality through optimized aberration correction.

Abstract

The joint design of the optical system and the downstream algorithm is a challenging and promising task. Due to the demand for balancing the global optimal of imaging systems and the computational cost of physical simulation, existing methods cannot achieve efficient joint design of complex systems such as smartphones and drones. In this work, starting from the perspective of the optical design, we characterize the optics with separated aberrations. Additionally, to bridge the hardware and software without gradients, an image simulation system is presented to reproduce the genuine imaging procedure of lenses with large field-of-views. As for aberration correction, we propose a network to perceive and correct the spatially varying aberrations and validate its superiority over state-of-the-art methods. Comprehensive experiments reveal that the preference for correcting separated aberrations in joint design is as follows: longitudinal chromatic aberration, lateral chromatic aberration, spherical aberration, field curvature, and coma, with astigmatism coming last. Drawing from the preference, a 10% reduction in the total track length of the consumer-level mobile phone lens module is accomplished. Moreover, this procedure spares more space for manufacturing deviations, realizing extreme-quality enhancement of computational photography. The optimization paradigm provides innovative insight into the practical joint design of sophisticated optical systems and post-processing algorithms.