High-quality phase imaging by phase-shifting digital holography and deep learning

Quantitative phase imaging (QPI) technology is widely used in biomedical imaging and other fields because it can realize exact imaging for transparent phase-type samples, which is of great research significance. The complex amplitude distribution of the object wave obtained by phase-shifting digital holography (PSDH) reproduction can provide phase information for QPI, but its existence of phase wrapping and other problems limits its practical application. Although the traditional phase unwrapping algorithm provides a solution, it has problems such as low unwrapping accuracy or long time running. To solve these problems in QPI, a high-quality phase imaging (HQPI) method by PSDH and deep learning (DL) is proposed, where QPI is achieved by extracting the unknown phase shift using a generalized non-iterative phase shift extraction algorithm and unwrapping the wrapped phase by a DL network. Both numerical simulations and optical experiments verify the feasibility of the method. By comparing with the traditional phase unwrapping algorithm, it is demonstrated that the DL unwrapping method has higher unwrapping accuracy and more efficiency. The results show that the method of HQPI is capable of realizing comparatively fast and accurate QPI. (c) 2024 Optica Publishing Group