Design of compact off-axis freeform imaging systems based on optical-digital joint optimization

Area of Science:

• Optics
• Computer Vision
• Optical Engineering

Background:

• Freeform optical surfaces reduce imaging system size and weight.
• Traditional design methods struggle with ultra-compact or simplified systems.
• Digital image processing can compensate for optical system limitations.

Purpose of the Study:

• To propose a novel optical-digital joint design process for compact off-axis freeform imaging systems.
• To integrate geometric freeform system design with neural network-based image recovery.
• To demonstrate the feasibility of designing ultra-compact and simplified freeform imaging systems.

Main Methods:

• Developed a joint design framework integrating geometric optical design and neural network image recovery.
• Utilized ray tracing and image simulation for system analysis.
• Established a loss function to optimize both optical design and image recovery.
• Applied the method to design off-axis, nonsymmetric systems with multiple freeform surfaces.

Main Results:

• Successfully designed a significantly smaller freeform three-mirror system compared to traditional designs.
• Developed a freeform two-mirror system, further reducing element count.
• Achieved ultra-compact and simplified system structures.
• Demonstrated good quality of recovered images from the designed systems.

Conclusions:

• The optical-digital joint design process enables the creation of ultra-compact and simplified freeform imaging systems.
• This integrated approach overcomes limitations of traditional freeform design for extreme miniaturization.
• The method is effective for complex, off-axis, nonsymmetric optical systems.