TR2019-090
Learning-Based Shadow Mitigation for Terahertz Multi-Layer Imaging
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- , "Learning-Based Shadow Mitigation for Terahertz Multi-Layer Imaging", International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz), DOI: 10.1109/IRMMW-THz.2019.8874429, September 2019.BibTeX TR2019-090 PDF
- @inproceedings{Wang2019sep,
- author = {Wang, Pu and Koike-Akino, Toshiaki and Bose, Arindam and Ma, Rui and Orlik, Philip V. and Tsujita, Wataru and Sadamoto, Kota and Tsutada, Hiroyuki and Soltanalian, Mojtaba},
- title = {{Learning-Based Shadow Mitigation for Terahertz Multi-Layer Imaging}},
- booktitle = {International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz)},
- year = 2019,
- month = sep,
- doi = {10.1109/IRMMW-THz.2019.8874429},
- issn = {2162-2035},
- isbn = {978-1-5386-8285-2},
- url = {https://www.merl.com/publications/TR2019-090}
- }
- , "Learning-Based Shadow Mitigation for Terahertz Multi-Layer Imaging", International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz), DOI: 10.1109/IRMMW-THz.2019.8874429, September 2019.
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Abstract:
This paper proposes a learning-based approach to mitigate the shadow effect in the pixel domain for Terahertz Time-Domain Spectroscopy (THz-TDS) multi-layer imaging. Compared with model-based approaches, this learning-based approach requires no prior knowledge of material properties of the sample. Preliminary simulations confirm the effectiveness of the proposed method.