Coded diﬀraction pattern phase retrieval with green noise masks

Qiuliang Ye; Chris Y.H. Chan; Michael G. Somekh; Daniel P.K. Lun

doi:10.1117/12.2626221

30 April 2022 Coded diﬀraction pattern phase retrieval with green noise masks

Qiuliang Ye, Chris Y.H. Chan, Michael G. Somekh, Daniel P.K. Lun

Proceedings Volume 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022; 121770V (2022) https://doi.org/10.1117/12.2626221
Event: International Workshop on Advanced Imaging Technology 2022 (IWAIT 2022), 2022, Hong Kong, China

Abstract

Coded-diffraction-pattern phase retrieval algorithms enhance performance with the help of random masks. However, traditional methods only focus on the randomness of the masks and disregard their non-bandlimited characteristics. The intensity measurements thus include plenty of high-frequency components outside the consideration of phase retrieval algorithm and lead to degraded performance. This article presents a green noise binary masking technique to substantially reduce the high-frequency components of the masks while meeting the randomization criterion. In addition, a novel phase retrieval algorithm is proposed to incorporate arbitrary denoising algorithms as prior based on the plug-and-plug framework. Simulation and experimental results show that the proposed green noise-masking technique and the plug-and-play reconstruction algorithm outperform the traditional methods in phase retrieval.

Citation Download Citation

Qiuliang Ye, Chris Y.H. Chan, Michael G. Somekh, and Daniel P.K. Lun "Coded diﬀraction pattern phase retrieval with green noise masks", Proc. SPIE 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022, 121770V (30 April 2022); https://doi.org/10.1117/12.2626221

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