IEICE TRANSACTIONS on Information
A Compressive Regularization Imaging Algorithm for Millimeter-Wave SAIR
Summary :
Aperture synthesis technology represents an effective approach to millimeter-wave radiometers for high-resolution observations. However, the application of synthetic aperture imaging radiometer (SAIR) is limited by its large number of antennas, receivers and correlators, which may increase noise and cause the image distortion. To solve those problems, this letter proposes a compressive regularization imaging algorithm, called CRIA, to reconstruct images accurately via combining the sparsity and the energy functional of target space. With randomly selected visibility samples, CRIA employs l1 norm to reconstruct the target brightness temperature and l2 norm to estimate the energy functional of it simultaneously. Comparisons with other algorithms show that CRIA provides higher quality target brightness temperature images at a lower data level.
- Publication
- IEICE TRANSACTIONS on Information Vol.E98-D No.8 pp.1609-1612
- Publication Date
- 2015/08/01
- Publicized
- 2015/05/07
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2014EDL8256
- Type of Manuscript
- LETTER
- Category
- Image Processing and Video Processing
Authors
Yilong ZHANG
Nanjing University of Science and Technology
Yuehua LI
Nanjing University of Science and Technology
Guanhua HE
Huaihai Industrial Group Co., LTD.
Sheng ZHANG
Huaihai Industrial Group Co., LTD.
Keyword
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Yilong ZHANG, Yuehua LI, Guanhua HE, Sheng ZHANG, "A Compressive Regularization Imaging Algorithm for Millimeter-Wave SAIR" in IEICE TRANSACTIONS on Information,
vol. E98-D, no. 8, pp. 1609-1612, August 2015, doi: 10.1587/transinf.2014EDL8256.
Abstract: Aperture synthesis technology represents an effective approach to millimeter-wave radiometers for high-resolution observations. However, the application of synthetic aperture imaging radiometer (SAIR) is limited by its large number of antennas, receivers and correlators, which may increase noise and cause the image distortion. To solve those problems, this letter proposes a compressive regularization imaging algorithm, called CRIA, to reconstruct images accurately via combining the sparsity and the energy functional of target space. With randomly selected visibility samples, CRIA employs l1 norm to reconstruct the target brightness temperature and l2 norm to estimate the energy functional of it simultaneously. Comparisons with other algorithms show that CRIA provides higher quality target brightness temperature images at a lower data level.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2014EDL8256/_p
Copy
@ARTICLE{e98-d_8_1609,
author={Yilong ZHANG, Yuehua LI, Guanhua HE, Sheng ZHANG, },
journal={IEICE TRANSACTIONS on Information},
title={A Compressive Regularization Imaging Algorithm for Millimeter-Wave SAIR},
year={2015},
volume={E98-D},
number={8},
pages={1609-1612},
abstract={Aperture synthesis technology represents an effective approach to millimeter-wave radiometers for high-resolution observations. However, the application of synthetic aperture imaging radiometer (SAIR) is limited by its large number of antennas, receivers and correlators, which may increase noise and cause the image distortion. To solve those problems, this letter proposes a compressive regularization imaging algorithm, called CRIA, to reconstruct images accurately via combining the sparsity and the energy functional of target space. With randomly selected visibility samples, CRIA employs l1 norm to reconstruct the target brightness temperature and l2 norm to estimate the energy functional of it simultaneously. Comparisons with other algorithms show that CRIA provides higher quality target brightness temperature images at a lower data level.},
keywords={},
doi={10.1587/transinf.2014EDL8256},
ISSN={1745-1361},
month={August},}
Copy
TY - JOUR
TI - A Compressive Regularization Imaging Algorithm for Millimeter-Wave SAIR
T2 - IEICE TRANSACTIONS on Information
SP - 1609
EP - 1612
AU - Yilong ZHANG
AU - Yuehua LI
AU - Guanhua HE
AU - Sheng ZHANG
PY - 2015
DO - 10.1587/transinf.2014EDL8256
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E98-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2015
AB - Aperture synthesis technology represents an effective approach to millimeter-wave radiometers for high-resolution observations. However, the application of synthetic aperture imaging radiometer (SAIR) is limited by its large number of antennas, receivers and correlators, which may increase noise and cause the image distortion. To solve those problems, this letter proposes a compressive regularization imaging algorithm, called CRIA, to reconstruct images accurately via combining the sparsity and the energy functional of target space. With randomly selected visibility samples, CRIA employs l1 norm to reconstruct the target brightness temperature and l2 norm to estimate the energy functional of it simultaneously. Comparisons with other algorithms show that CRIA provides higher quality target brightness temperature images at a lower data level.
ER -
English
