Terahertz Image Restoration with 'Zero-Shot' Super-Resolution

Zhongde Han, Weidong Hu, Yade Li, Zhihao Xu, Yunzhang Zhao, Jiaqi Ni, Leo Ligthart

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The spatial resolution of terahertz (THz) image is often degraded by many factors during the imaging process. Therefore, a 'Zero-Shot' super-resolution CNN framework, which is trained only by the input image itself, is proposed to cope with those degradation factors. With this unsupervised framework, the restoration level of the CNN can be flexibly adjusted based on the input THz image in order to achieve the best restoration effect. Experimental results on both the simulated data and real tested THz data have proved the effectiveness of our method.

Original languageEnglish
Title of host publication2020 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728181813
DOIs
Publication statusPublished - 13 Dec 2020
Event2020 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2020 - Fuzhou, Fujian, China
Duration: 13 Dec 202016 Dec 2020

Publication series

Name2020 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2020 - Proceedings

Conference

Conference2020 Cross Strait Radio Science and Wireless Technology Conference, CSRSWTC 2020
Country/TerritoryChina
CityFuzhou, Fujian
Period13/12/2016/12/20

Keywords

  • Zero-Shot super-resolution
  • image restoration
  • point-spread-function (PSF)
  • spatial resolution

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