Objective and efficient terahertz signal denoising by transfer function reconstruction
As an essential processing step in many disciplines, signal denoising efficiently improves data quality without extra cost. However, it is relatively under-utilized for terahertz spectroscopy. The major technique reported uses wavelet denoising in the time-domain, which has a fuzzy physical meaning...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2020-05-01
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| Series: | APL Photonics |
| Online Access: | http://dx.doi.org/10.1063/5.0002968 |
| _version_ | 1829100795103019008 |
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| author | Xuequan Chen Qiushuo Sun Rayko I. Stantchev Emma Pickwell-MacPherson |
| author_facet | Xuequan Chen Qiushuo Sun Rayko I. Stantchev Emma Pickwell-MacPherson |
| author_sort | Xuequan Chen |
| collection | DOAJ |
| description | As an essential processing step in many disciplines, signal denoising efficiently improves data quality without extra cost. However, it is relatively under-utilized for terahertz spectroscopy. The major technique reported uses wavelet denoising in the time-domain, which has a fuzzy physical meaning and limited performance in low-frequency and water-vapor regions. Here, we work from a new perspective by reconstructing the transfer function to remove noise-induced oscillations. The method is fully objective without a need for defining a threshold. Both reflection imaging and transmission imaging were conducted. The experimental results show that both low- and high-frequency noise and the water-vapor influence were efficiently removed. The spectrum accuracy was also improved, and the image contrast was significantly enhanced. The signal-to-noise ratio of the leaf image was increased up to 10 dB, with the 6 dB bandwidth being extended by over 0.5 THz. |
| first_indexed | 2024-12-10T22:38:28Z |
| format | Article |
| id | doaj.art-383dc5cf353d462e9111b0428a0d44e4 |
| institution | Directory Open Access Journal |
| issn | 2378-0967 |
| language | English |
| last_indexed | 2024-12-10T22:38:28Z |
| publishDate | 2020-05-01 |
| publisher | AIP Publishing LLC |
| record_format | Article |
| series | APL Photonics |
| spelling | doaj.art-383dc5cf353d462e9111b0428a0d44e42022-12-22T01:30:47ZengAIP Publishing LLCAPL Photonics2378-09672020-05-0155056104056104-810.1063/5.0002968Objective and efficient terahertz signal denoising by transfer function reconstructionXuequan Chen0Qiushuo Sun1Rayko I. Stantchev2Emma Pickwell-MacPherson3Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong 999077, ChinaDepartment of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT, United KingdomDepartment of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong 999077, ChinaDepartment of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong 999077, ChinaAs an essential processing step in many disciplines, signal denoising efficiently improves data quality without extra cost. However, it is relatively under-utilized for terahertz spectroscopy. The major technique reported uses wavelet denoising in the time-domain, which has a fuzzy physical meaning and limited performance in low-frequency and water-vapor regions. Here, we work from a new perspective by reconstructing the transfer function to remove noise-induced oscillations. The method is fully objective without a need for defining a threshold. Both reflection imaging and transmission imaging were conducted. The experimental results show that both low- and high-frequency noise and the water-vapor influence were efficiently removed. The spectrum accuracy was also improved, and the image contrast was significantly enhanced. The signal-to-noise ratio of the leaf image was increased up to 10 dB, with the 6 dB bandwidth being extended by over 0.5 THz.http://dx.doi.org/10.1063/5.0002968 |
| spellingShingle | Xuequan Chen Qiushuo Sun Rayko I. Stantchev Emma Pickwell-MacPherson Objective and efficient terahertz signal denoising by transfer function reconstruction APL Photonics |
| title | Objective and efficient terahertz signal denoising by transfer function reconstruction |
| title_full | Objective and efficient terahertz signal denoising by transfer function reconstruction |
| title_fullStr | Objective and efficient terahertz signal denoising by transfer function reconstruction |
| title_full_unstemmed | Objective and efficient terahertz signal denoising by transfer function reconstruction |
| title_short | Objective and efficient terahertz signal denoising by transfer function reconstruction |
| title_sort | objective and efficient terahertz signal denoising by transfer function reconstruction |
| url | http://dx.doi.org/10.1063/5.0002968 |
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