Freeform optical design via surface type conversion: a dual-optimization strategy for miniaturized high-resolution imaging system

Abstract Conventional optical systems employing spherical and aspherical surfaces encounter constraints on variable parameters that limit both imaging performance and miniaturization potential. This study presents a systematic methodology for designing and optimizing freeform-based transmission imaging systems through surface type conversion techniques. The proposed framework integrates two advantages: one is an optimal multi-parameter optimization algorithm addressing surface parameter fitting problem, and the other is a comprehensive implementation framework for freeform optical system design, capitalizing on the augmented design flexibility afforded by freeform surface. Experimental validation through a prototype camera system demonstrates significant performance enhancements: grid distortion reduction from 2.21% to 1.38%, and improvement of edge field modulation transfer function at 110 lp mm −1 from 0.26 to 0.47. This work establishes a generalized design paradigm for freeform optics, providing a systematic framework that reconciles optical performance optimization with structural miniaturization requirements, thereby advancing the development of compact high-performance optical system.