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Deep Learning Optimized Terahertz Single-Pixel Imaging
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DOI：10.1109/TTHZ.2021.3132160.png)
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Abstract
En 中文
In this article, we demonstrate an efficient terahertz single-pixel imaging system incorporating deep learning networks. Experimental results show that by combining a Hadamard single-pixel imaging system with the deep learning network, the sampling time per pattern can be reduced to 1/20 of the conventional system and the number of Hadamard patterns can be reduced to 10% of the pixels while maintaining high image quality with acceptable signal-to-noise ratio above 20 dB and structural similarity of more than 0.85. We thus expect this article to advance the development of a real-time terahertz single-pixel imaging system and promote its applications.
Keywords:
Imaging
Deep learning
Terahertz wave imaging
Image reconstruction
Laser beams
Measurement by laser beam
Detectors
Deep learning networks
hadamard single-pixel imaging
high image quality
terahertz
Journal
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4
Papers:
1.5K
Citations:
3.6K