In this Letter, we introduce a computer-generated hologram (CGH) optimization technique that can control the randomness of the reconstructed phase. The phase randomness significantly affects the eyebox size and depth of field in holographic near-eye displays. Our proposal is to synthesize the CGH through the sum of two terms computed from the target scene with a random phase. We set a weighting pattern for summation as the optimization variable, which enables the CGH to reflect the random phase during optimization. We evaluate the proposed algorithm on single-depth and multi-depth contents, and the performance is validated via simulations and experiments.

中文翻译：

---

具有相位随机性控制的计算机生成全息图的优化

在这封信中，我们介绍了一种可以控制重建相位随机性的计算机生成全息图 (CGH) 优化技术。相位随机性显着影响全息近眼显示器中的眼框大小和景深。我们的建议是通过从具有随机相位的目标场景计算的两项之和来合成 CGH。我们将求和的加权模式设置为优化变量，使 CGH 能够反映优化过程中的随机相位。我们在单深度和多深度内容上评估了所提出的算法，并通过模拟和实验验证了其性能。