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4 October 2023 From spatial to spatiotemporal compressive sensing for high-speed quantitative phase imaging
Yunhui Gao, Liangcai Cao
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Proceedings Volume PC12746, SPIE-CLP Conference on Advanced Photonics 2023; PC127460K (2023) https://doi.org/10.1117/12.2685811
Event: SPIE-CLP Conference on Advanced Photonics, 2023, San Diego, California, United States
Abstract
Quantitative phase imaging (QPI) techniques can reveal the subtle interactions between light and the physical objects. However, the reconstruction problem is inherently ill-posed because only intensity can be directly recorded by the image sensor. Here, we propose a general computational framework for single-shot, high-quality QPI by exploring the sparsity features of the complex sample field. The resulting image reconstruction algorithm is highly scalable and features theoretically tractable convergence behaviors. We successfully demonstrate single-shot QPI in various metrological and biomedical applications. The proposed algorithmic framework can also be extended to exploit spatiotemporal priors and diversity measurement schemes, thereby pushing the imaging performance toward higher limits.
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(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Yunhui Gao and Liangcai Cao "From spatial to spatiotemporal compressive sensing for high-speed quantitative phase imaging", Proc. SPIE PC12746, SPIE-CLP Conference on Advanced Photonics 2023, PC127460K (4 October 2023); https://doi.org/10.1117/12.2685811
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KEYWORDS
Phase imaging
Phase retrieval
Reconstruction algorithms
Temporal resolution
Biological samples
Image restoration
Imaging systems
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