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Single-shot inline holography using a physics-aware diffusion model
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DOI：10.1364/OE.517233.png)
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Among holographic imaging configurations, inline holography excels in its compact design and portability, making it the preferred choice for on -site or field applications with unique imaging requirements. However, effectively holographic reconstruction from a single -shot measurement remains a challenge. While several approaches have been proposed, our novel unsupervised algorithm, the physics -aware diffusion model for digital holographic reconstruction (PadDH), offers distinct advantages. By seamlessly integrating physical information with a pre -trained diffusion model, PadDH overcomes the need for a holographic training dataset and significantly reduces the number of parameters involved. Through comprehensive experiments using both synthetic and experimental data, we validate the capabilities of PadDH in reducing twin -image contamination and generating high -quality reconstructions. Our work represents significant advancements in unsupervised holographic imaging by harnessing the full potential of the pre -trained diffusion prior.
Keyword:
PHASE RETRIEVAL
DEEP
NET
期刊
IF:
3.3
论文数:
6.1W
被引数:
14.3W
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引用论文
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