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Plug-and-play algorithms for single-pixel imaging
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AI
DOI：10.1016/j.optlaseng.2022.106970.png)
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Single-pixel imaging (SPI) captures images using a photodiode, which has advantages of low cost and high signalto-noise ratio compared with sensor arrays. When combining with compressed sensing (CS), images can be recovered from fewer measurements in spite of the ill-posed problem. The most commonly used SPI reconstruction algorithms are model-based methods, which usually utilize the hand-crafted prior and limit image quality in the case of under-sampling. In this paper, we propose a novel compressive imaging approach for SPI based on Plug-and-Play (PnP) algorithms. It well employs deep denoiser prior and combines with model-based algorithm advantage. Extensive results on both simulation and real data show that the proposed PnP-based SPI reconstruction method outperforms state-of-the-art SPI algorithms and realizes higher quality image reconstruction.
Keyword:
Computational Imaging
Single-pixel imaging
Plug-and-Play
Image reconstruction
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3.7
论文数:
7.3K
被引数:
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