论文标题
使用绿色噪声二进制口罩的强大相位检索
Robust Phase Retrieval with Green Noise Binary Masks
论文作者
论文摘要
使用预定义的光面膜检索可以提供额外的约束，从而提高性能。优化理论的最新进展证明了在相检索算法中随机掩模的优越性。但是，传统的方法仅着眼于面具的随机性，但忽略了它们的非限制性。当在重建过程中使用这些掩码进行相检索时，通常在过程中删除掩模的高频部分，从而导致性能降解。基于数字硬质的概念，本文提出了一种绿色噪声二进制掩蔽方案，该方案可以大大降低掩模的高频含量，同时满足随机性要求。实验结果表明，在使用基于DMD的编码衍射模式相检索系统中，提出的绿色噪声二进制掩蔽方案优于传统的屏蔽方案。
Phase retrieval with pre-defined optical masks can provide extra constraint and thus achieve improved performance. The recent progress in optimization theory demonstrates the superiority of random masks in phase retrieval algorithms. However, traditional approaches just focus on the randomness of the masks but ignore their non-bandlimited nature. When using these masks in the reconstruction process for phase retrieval, the high frequency part of the masks is often removed in the process and thus leads to degraded performance. Based on the concept of digital halftoning, this paper proposes a green noise binary masking scheme which can greatly reduce the high frequency content of the masks while fulfilling the randomness requirement. The experimental results show that the proposed green noise binary masking scheme outperform the traditional ones when using in a DMD-based coded diffraction pattern phase retrieval system.
