Quality improvement of unfiltered holography by optimizing high diffraction orders with fill factor

Area of Science:

• Optics and Photonics
• Computational Imaging

Background:

• Computer-generated holography (CGH) faces challenges with high diffraction orders (HDOs) from pixelated spatial light modulators (SLMs).
• Existing solutions often require bulky optical filtering systems to manage HDOs.
• The prior high-order gradient descent (HOGD) algorithm optimized HDOs for compact displays but neglected SLM fill factor, limiting optical quality.

Purpose of the Study:

• To introduce a novel algorithm that improves the optical quality of unfiltered holography.
• To address the limitations of previous methods by incorporating the SLM fill factor into the optimization process.

Main Methods:

• Development of the fill factor-based high-order gradient descent (FF-HOGD) algorithm.
• Integration of the SLM fill factor parameter into the HOGD optimization framework.
• Validation through numerical simulations and optical experiments.

Main Results:

• The FF-HOGD algorithm successfully incorporates the fill factor into holographic optimization.
• Demonstrated significant improvement in optical quality compared to previous unfiltered holography methods.
• Numerical and experimental results confirm the effectiveness of the FF-HOGD approach.

Conclusions:

• The FF-HOGD algorithm offers a superior method for enhancing unfiltered holography.
• Accounting for the SLM fill factor is crucial for achieving high-quality holographic displays.
• This advancement enables more compact and higher-quality holographic display technologies.