IEICE TRANSACTIONS on Information
Fully Connected Imaging Network for Near-Field Synthetic Aperture Interferometric Radiometer
Summary :
Millimeter wave synthetic aperture interferometric radiometers (SAIR) are very powerful instruments, which can effectively realize high-precision imaging detection. However due to the existence of interference factor and complex near-field error, the imaging effect of near-field SAIR is usually not ideal. To achieve better imaging results, a new fully connected imaging network (FCIN) is proposed for near-field SAIR. In FCIN, the fully connected network is first used to reconstruct the image domain directly from the visibility function, and then the residual dense network is used for image denoising and enhancement. The simulation results show that the proposed FCIN method has high imaging accuracy and shorten imaging time.
- Publication
- IEICE TRANSACTIONS on Information Vol.E105-D No.5 pp.1120-1124
- Publication Date
- 2022/05/01
- Publicized
- 2022/02/09
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2021EDL8105
- Type of Manuscript
- LETTER
- Category
- Artificial Intelligence, Data Mining
Authors
Zhimin GUO
Nanjing University of Posts and Telecommunications
Jianfei CHEN
Nanjing University of Posts and Telecommunications
Sheng ZHANG
Nanjing University of Posts and Telecommunications
Keyword
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Zhimin GUO, Jianfei CHEN, Sheng ZHANG, "Fully Connected Imaging Network for Near-Field Synthetic Aperture Interferometric Radiometer" in IEICE TRANSACTIONS on Information,
vol. E105-D, no. 5, pp. 1120-1124, May 2022, doi: 10.1587/transinf.2021EDL8105.
Abstract: Millimeter wave synthetic aperture interferometric radiometers (SAIR) are very powerful instruments, which can effectively realize high-precision imaging detection. However due to the existence of interference factor and complex near-field error, the imaging effect of near-field SAIR is usually not ideal. To achieve better imaging results, a new fully connected imaging network (FCIN) is proposed for near-field SAIR. In FCIN, the fully connected network is first used to reconstruct the image domain directly from the visibility function, and then the residual dense network is used for image denoising and enhancement. The simulation results show that the proposed FCIN method has high imaging accuracy and shorten imaging time.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2021EDL8105/_p
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@ARTICLE{e105-d_5_1120,
author={Zhimin GUO, Jianfei CHEN, Sheng ZHANG, },
journal={IEICE TRANSACTIONS on Information},
title={Fully Connected Imaging Network for Near-Field Synthetic Aperture Interferometric Radiometer},
year={2022},
volume={E105-D},
number={5},
pages={1120-1124},
abstract={Millimeter wave synthetic aperture interferometric radiometers (SAIR) are very powerful instruments, which can effectively realize high-precision imaging detection. However due to the existence of interference factor and complex near-field error, the imaging effect of near-field SAIR is usually not ideal. To achieve better imaging results, a new fully connected imaging network (FCIN) is proposed for near-field SAIR. In FCIN, the fully connected network is first used to reconstruct the image domain directly from the visibility function, and then the residual dense network is used for image denoising and enhancement. The simulation results show that the proposed FCIN method has high imaging accuracy and shorten imaging time.},
keywords={},
doi={10.1587/transinf.2021EDL8105},
ISSN={1745-1361},
month={May},}
Copy
TY - JOUR
TI - Fully Connected Imaging Network for Near-Field Synthetic Aperture Interferometric Radiometer
T2 - IEICE TRANSACTIONS on Information
SP - 1120
EP - 1124
AU - Zhimin GUO
AU - Jianfei CHEN
AU - Sheng ZHANG
PY - 2022
DO - 10.1587/transinf.2021EDL8105
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E105-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2022
AB - Millimeter wave synthetic aperture interferometric radiometers (SAIR) are very powerful instruments, which can effectively realize high-precision imaging detection. However due to the existence of interference factor and complex near-field error, the imaging effect of near-field SAIR is usually not ideal. To achieve better imaging results, a new fully connected imaging network (FCIN) is proposed for near-field SAIR. In FCIN, the fully connected network is first used to reconstruct the image domain directly from the visibility function, and then the residual dense network is used for image denoising and enhancement. The simulation results show that the proposed FCIN method has high imaging accuracy and shorten imaging time.
ER -
English
