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Physics-driven deep learning enables temporal compressive coherent diffraction imaging
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DOI：10.1364/OPTICA.454582.png)
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Abstract
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Coherent diffraction imaging (CDI), as a lensless imaging technique, can achieve a high-resolution image with intensity and phase information from a diffraction pattern. To capture high-speed and high-spatial-resolution scenes, we propose a temporal compressive CDI system. A two-step algorithm using physics-driven deep-learning networks is developed for multi-frame spectra reconstruction and phase retrieval. Experimental results demonstrate that our system can reconstruct up to eight frames from a snapshot measurement. Our results offer the potential to visualize the dynamic process of molecules with large fields of view and high spatial and temporal resolutions. (c) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
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