kqwang/DLPR
Example code for data-driven and physics-driven deep learning phase recovery
This project helps optical scientists and engineers recover the missing phase information from recorded light intensity patterns (holograms). It takes images of holograms as input and outputs the corresponding phase maps, which are crucial for understanding object properties or reconstructing 3D images. Researchers and practitioners in fields like microscopy, imaging, or optical metrology would find this useful for analyzing their optical data.
No commits in the last 6 months.
Use this if you need to reconstruct phase information from optical intensity measurements using various deep learning techniques.
Not ideal if you are looking for a plug-and-play software tool without needing to work with Python code or manage deep learning environments.
Stars
41
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2
Language
Python
License
MIT
Category
Last pushed
Aug 28, 2025
Commits (30d)
0
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