Dual-plane coupled phase retrieval for non-prior holographic imaging

Accurate depiction of waves in temporal and spatial is essential to the investigation of interactions between physical objects and waves. Digital holography (DH) can perform quantitative analysis of wave–matter interactions. Full detector-bandwidth reconstruction can be realized based on in-line DH....

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Bibliographic Details
Published inPhotoniX Vol. 3; no. 1; pp. 1 - 16
Main Authors Huang, Zhengzhong, Memmolo, Pasquale, Ferraro, Pietro, Cao, Liangcai
Format Journal Article
LanguageEnglish
Published Singapore Springer Singapore 28.01.2022
Springer Nature B.V
SpringerOpen
Subjects
Bandwidths
Cameras
Digital holography
Engineering
Full bandwidth
In-line holography
Methods
Microwaves
Off-axis holography
Optimization
Phase retrieval
Propagation
RF and Optical Engineering
Sensors
In-line holography
Digital holography
Off-axis holography
Phase retrieval
Full bandwidth
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Summary:Accurate depiction of waves in temporal and spatial is essential to the investigation of interactions between physical objects and waves. Digital holography (DH) can perform quantitative analysis of wave–matter interactions. Full detector-bandwidth reconstruction can be realized based on in-line DH. But the overlapping of twin images strongly prevents quantitative analysis. For off-axis DH, the object wave and the detector bandwidth need to satisfy certain conditions to perform reconstruction accurately. Here, we present a reliable approach involving a coupled configuration for combining two in-line holograms and one off-axis hologram, using a rapidly converging iterative procedure based on two-plane coupled phase retrieval (TwPCPR) method. It realizes a fast-convergence holographic calculation method. High-resolution and full-field reconstruction by exploiting the full bandwidth are demonstrated for complex-amplitude reconstruction. Off-axis optimization phase provides an effective initial guess to avoid stagnation and minimize the required measurements of multi-plane phase retrieval. The proposed strategy works well for more extended samples without any prior assumptions of the objects including support, non-negative, sparse constraints, etc. It helps to enhance and empower applications in wavefront sensing, computational microscopy and biological tissue analysis.
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ISSN:2662-1991
2662-1991
DOI:10.1186/s43074-021-00046-w