Novel approach based on stochastic gradient descent for controlling the reconstructed phase randomness of computer-generated holograms
Chenhang Shen, Yuhang Zheng, Zichun Le
Abstract
Depth of field, as one of the essential adjustment cues, affects the user experience and restricts the application of holographic displays. However, it is often underappreciated in modern holographic displays. In this study, we propose a novel computer-generated hologram (CGH) method that uses a pre-calculation procedure and a standard deviation-based loss function to generate realistic depth-of-field effects. The depth-of-field size is adjusted by controlling the randomness of the reconstructed phase. The ability of the proposed algorithm to control the reconstructed phase randomness was confirmed. Finally, a holographic display prototype was built to demonstrate the proposed method experimentally. The experimental results were consistent with the simulation results. Our findings may open up a new perspective on the application of existing stochastic gradient descent (SGD) algorithms to traditional methods for image quality optimization by adding random phases.