Terahertz Image Restoration with "Zero-Shot" Super-resolution

被引：0

作者：

Han, Zhongde ^{[1
]}

Hu, Weidong ^{[1
]}

Li, Yade ^{[1
]}

Xu, Zhihao ^{[1
]}

Zhao, Yunzhang ^{[1
]}

Ni, Jiaqi ^{[1
]}

Ligthart, Leo ^{[2
]}

机构：

[1] Beijing Inst Technol, Beijing Key Lab Millimeter Wave & Terahertz Techn, Beijing, Peoples R China

[2] Delft Univ Technol, Fac Elect Engn, NL-2600 GA Delft, Netherlands

来源：

2020 CROSS STRAIT RADIO SCIENCE & WIRELESS TECHNOLOGY CONFERENCE, CSRSWTC | 2020年

基金：

国家重点研发计划;

关键词：

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

D O I：

10.1109/CSRSWTC50769.2020.9372649

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页数：3

共 6 条

[1] Mathematical Modeling of THz Point Spread Function and Simulation of THz Imaging Systems [J].