Power-balanced hybrid optics boosted design for achromatic extended depth-of-field imaging via optimized mixed OTF

Area of Science:

• Optical Engineering
• Computational Imaging
• Diffractive Optics

Background:

• Traditional optical systems face limitations in focal depth and chromatic aberration.
• Computational imaging offers potential for enhanced optical performance through digital processing.

Purpose of the Study:

• To develop and evaluate a power-balanced hybrid optical imaging system combining refractive and diffractive elements.
• To introduce and optimize a multilevel phase mask (MPM) for improved imaging characteristics.
• To achieve superior image reconstruction quality, especially for off-focus distances.

Main Methods:

• Designed a hybrid optical imaging system with a refractive lens and a multilevel phase mask (MPM).
• Developed a differentiable image formation model for joint optimization of optical and imaging parameters using neural networks.
• Optimized a depth-invariant Wiener-like optical transfer function (OTF) for image reconstruction.
• Conducted numerical and experimental comparisons with lensless and lens-only systems.

Main Results:

• The proposed hybrid system demonstrates a long focal depth and low chromatic aberrations.
• The optimized system, using a depth-invariant OTF, significantly improves reconstruction quality for off-focus images compared to counterparts.
• Optimization of optical power balance, Fresnel order, and quantization levels enhanced performance, achieving up to 5 dB PSNR improvement over lensless setups.

Conclusions:

• The power-balanced hybrid optical imaging system with a diffractive computational camera offers superior performance.
• Joint optimization of optical design (MPM, power balance) and image reconstruction (OTF) is crucial for advanced imaging.
• This approach provides a promising solution for achieving high-quality imaging over extended depth-of-field ranges.