Volume 15 Issue 3
May  2022
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Chinese Optics  > 2022  >  15(3): 405-417.
CAO Bing-hua, ZHANG Yu-meng, FAN Meng-bao, SUN Feng-shan, LIU Lin. Research progress of terahertz super-resolution imaging[J]. Chinese Optics, 2022, 15(3): 405-417. doi: 10.37188/CO.2021-0198
Citation: CAO Bing-hua, ZHANG Yu-meng, FAN Meng-bao, SUN Feng-shan, LIU Lin. Research progress of terahertz super-resolution imaging[J]. Chinese Optics, 2022, 15(3): 405-417. doi: 10.37188/CO.2021-0198
shu

Research progress of terahertz super-resolution imaging

  • 1.

    School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221000, China

  • 2.

    School of Mechatronic Engineering, China University of Mining and Technology, Xuzhou 221000, China

  • 3.

    Beijing Institute of Aerospace Metrology and Measurement Technology, Bejing 100076, China

Funds:  Supported by National Natural Science Foundtion of China (No. 62071471); Natural Science Foundation of Jiangsu Province (No. BK20211244)
More Information
  • Corresponding author: caobinghua@cumt.edu.cn
  • Received Date: 12 Nov 2021
  • Rev Recd Date: 13 Dec 2021
  • Accepted Date: 21 Jan 2022
    • Available Online: 27 Jan 2022
  • Publish Date: 20 May 2022
    Abstract
  • Terahertz (THz) imaging technology has recently become one of the most cutting-edge technologies in many fields and has made great progress in its development over the past two decades. With the increasing demands of scientific research, medical treatment, military and industrial applications, high-resolution THz images have become indispensable. To obtain high-resolution THz images, super-resolution imaging has become a research hotspot. In this paper, the imaging methods of a THz system are reviewed, including continuous wave imaging and pulse wave imaging. On this basis, THz super-resolution imaging systems and THz signal processing technologies are described in detail. The super-resolution imaging systems include near-field imaging, super lens and terajet effect, etc. The THz signal processing technologies could be grouped as either super-resolution reconstruction and convolution calculations. Finally, the shortcomings of current super-resolution imaging technologies were discussed. There are still some bottlenecks that need to be resolved such as the high manufacturing process requirements of the system, the slow acquisition speed, and the low resolution of the learning samples used to reconstruct images. With this analysis, the research direction of super-resolution imaging is proposed.

     

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