Abstract
We approach to the problem of wave-front reconstruction via phase unwrapping of interferograms observed by interferometric synthetic aperture radar (SAR), from the viewpoints of Bayesian statistical inference and compressed sensing. For this purpose, we apply sparse representation for compressed sensing to the Bayesian wave-front reconstruction model from SAR interferograms by Saika and Uezu [1]. In the formulation of the problem taking sparse representation into account, the MAP estimate is found to lead to a phase unwrapping algorithm which can be interpreted as a quadratic programming problem. Numerical experiments on an artificial wave-front make it clear that the algorithm effectively removes noise to reconstruct the wave-front, although it suffers from the errors similar to block noise in image processing.
| Original language | English |
|---|---|
| Title of host publication | ICCAS 2017 - 2017 17th International Conference on Control, Automation and Systems - Proceedings |
| Publisher | IEEE Computer Society |
| Pages | 989-993 |
| Number of pages | 5 |
| Volume | 2017-October |
| ISBN (Electronic) | 9788993215137 |
| DOIs | |
| Publication status | Published - Dec 13 2017 |
| Event | 17th International Conference on Control, Automation and Systems, ICCAS 2017 - Jeju, Korea, Republic of Duration: Oct 18 2017 → Oct 21 2017 |
Other
| Other | 17th International Conference on Control, Automation and Systems, ICCAS 2017 |
|---|---|
| Country | Korea, Republic of |
| City | Jeju |
| Period | 10/18/17 → 10/21/17 |
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Keywords
- Bayesian inference
- Compressed sensing
- Phase unwrapping
- Remote sensing
- SAR
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Science Applications
- Control and Systems Engineering
- Electrical and Electronic Engineering
Cite this
Compressed sensing for phase unwrapping of interferometric SAR data. / Aida, Toshiaki.
ICCAS 2017 - 2017 17th International Conference on Control, Automation and Systems - Proceedings. Vol. 2017-October IEEE Computer Society, 2017. p. 989-993.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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TY - GEN
T1 - Compressed sensing for phase unwrapping of interferometric SAR data
AU - Aida, Toshiaki
PY - 2017/12/13
Y1 - 2017/12/13
N2 - We approach to the problem of wave-front reconstruction via phase unwrapping of interferograms observed by interferometric synthetic aperture radar (SAR), from the viewpoints of Bayesian statistical inference and compressed sensing. For this purpose, we apply sparse representation for compressed sensing to the Bayesian wave-front reconstruction model from SAR interferograms by Saika and Uezu [1]. In the formulation of the problem taking sparse representation into account, the MAP estimate is found to lead to a phase unwrapping algorithm which can be interpreted as a quadratic programming problem. Numerical experiments on an artificial wave-front make it clear that the algorithm effectively removes noise to reconstruct the wave-front, although it suffers from the errors similar to block noise in image processing.
AB - We approach to the problem of wave-front reconstruction via phase unwrapping of interferograms observed by interferometric synthetic aperture radar (SAR), from the viewpoints of Bayesian statistical inference and compressed sensing. For this purpose, we apply sparse representation for compressed sensing to the Bayesian wave-front reconstruction model from SAR interferograms by Saika and Uezu [1]. In the formulation of the problem taking sparse representation into account, the MAP estimate is found to lead to a phase unwrapping algorithm which can be interpreted as a quadratic programming problem. Numerical experiments on an artificial wave-front make it clear that the algorithm effectively removes noise to reconstruct the wave-front, although it suffers from the errors similar to block noise in image processing.
KW - Bayesian inference
KW - Compressed sensing
KW - Phase unwrapping
KW - Remote sensing
KW - SAR
UR - http://www.scopus.com/inward/record.url?scp=85044439932&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044439932&partnerID=8YFLogxK
U2 - 10.23919/ICCAS.2017.8204366
DO - 10.23919/ICCAS.2017.8204366
M3 - Conference contribution
AN - SCOPUS:85044439932
VL - 2017-October
SP - 989
EP - 993
BT - ICCAS 2017 - 2017 17th International Conference on Control, Automation and Systems - Proceedings
PB - IEEE Computer Society
ER -