Time-Regularized Blind Deconvolution Approach for Radio Interferometry

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Radio-interferometric imaging aims to estimate a sky intensity image from degraded undersampled Fourier measurements. At the dynamic range of interest to modern radio telescopes, the image reconstruction quality will be limited by the unknown time-dependent calibration kernels. Hence the need of performing joint image reconstruction and calibration, and consequently of solving a non-convex blind deconvolution problem. Extending our recent work where the calibration kernels are assumed to be smooth in space, we further assume in this work that the calibration kernels are smooth in time. In addition, an average sparsity prior is used for the estimation of the image of interest. The resulting high dimensional non-convex non-smooth minimization problem is then solved by leveraging an alternating forward-backward algorithm which benefits from well-established convergence guarantees. Our results show that time-regularization is effective in enhancing imaging quality.
LanguageEnglish
Title of host publication10th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2018)
PublisherIEEE
Pages475-479
Number of pages5
ISBN (Print)9781538647530
Publication statusPublished - 2018

Fingerprint

Deconvolution
Interferometry
Calibration
Image reconstruction
Radio telescopes
Imaging techniques

Keywords

  • Radio-interferometric imaging
  • Calibration
  • Alternating forward-backward approach

Cite this

Thouvenin, P-A., Repetti, A., Dabbech, A., & Wiaux, Y. (2018). Time-Regularized Blind Deconvolution Approach for Radio Interferometry. In 10th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2018) (pp. 475-479). IEEE.
Thouvenin, Pierre-Antoine ; Repetti, Audrey ; Dabbech, Arwa ; Wiaux, Yves. / Time-Regularized Blind Deconvolution Approach for Radio Interferometry. 10th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2018). IEEE, 2018. pp. 475-479
@inproceedings{bc8da6ec05ab430d85121ea96ad8213f,
title = "Time-Regularized Blind Deconvolution Approach for Radio Interferometry",
abstract = "Radio-interferometric imaging aims to estimate a sky intensity image from degraded undersampled Fourier measurements. At the dynamic range of interest to modern radio telescopes, the image reconstruction quality will be limited by the unknown time-dependent calibration kernels. Hence the need of performing joint image reconstruction and calibration, and consequently of solving a non-convex blind deconvolution problem. Extending our recent work where the calibration kernels are assumed to be smooth in space, we further assume in this work that the calibration kernels are smooth in time. In addition, an average sparsity prior is used for the estimation of the image of interest. The resulting high dimensional non-convex non-smooth minimization problem is then solved by leveraging an alternating forward-backward algorithm which benefits from well-established convergence guarantees. Our results show that time-regularization is effective in enhancing imaging quality.",
keywords = "Radio-interferometric imaging, Calibration, Alternating forward-backward approach",
author = "Pierre-Antoine Thouvenin and Audrey Repetti and Arwa Dabbech and Yves Wiaux",
year = "2018",
language = "English",
isbn = "9781538647530",
pages = "475--479",
booktitle = "10th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2018)",
publisher = "IEEE",
address = "United States",

}

Thouvenin, P-A, Repetti, A, Dabbech, A & Wiaux, Y 2018, Time-Regularized Blind Deconvolution Approach for Radio Interferometry. in 10th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2018). IEEE, pp. 475-479.

Time-Regularized Blind Deconvolution Approach for Radio Interferometry. / Thouvenin, Pierre-Antoine; Repetti, Audrey; Dabbech, Arwa; Wiaux, Yves.

10th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2018). IEEE, 2018. p. 475-479.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Time-Regularized Blind Deconvolution Approach for Radio Interferometry

AU - Thouvenin, Pierre-Antoine

AU - Repetti, Audrey

AU - Dabbech, Arwa

AU - Wiaux, Yves

PY - 2018

Y1 - 2018

N2 - Radio-interferometric imaging aims to estimate a sky intensity image from degraded undersampled Fourier measurements. At the dynamic range of interest to modern radio telescopes, the image reconstruction quality will be limited by the unknown time-dependent calibration kernels. Hence the need of performing joint image reconstruction and calibration, and consequently of solving a non-convex blind deconvolution problem. Extending our recent work where the calibration kernels are assumed to be smooth in space, we further assume in this work that the calibration kernels are smooth in time. In addition, an average sparsity prior is used for the estimation of the image of interest. The resulting high dimensional non-convex non-smooth minimization problem is then solved by leveraging an alternating forward-backward algorithm which benefits from well-established convergence guarantees. Our results show that time-regularization is effective in enhancing imaging quality.

AB - Radio-interferometric imaging aims to estimate a sky intensity image from degraded undersampled Fourier measurements. At the dynamic range of interest to modern radio telescopes, the image reconstruction quality will be limited by the unknown time-dependent calibration kernels. Hence the need of performing joint image reconstruction and calibration, and consequently of solving a non-convex blind deconvolution problem. Extending our recent work where the calibration kernels are assumed to be smooth in space, we further assume in this work that the calibration kernels are smooth in time. In addition, an average sparsity prior is used for the estimation of the image of interest. The resulting high dimensional non-convex non-smooth minimization problem is then solved by leveraging an alternating forward-backward algorithm which benefits from well-established convergence guarantees. Our results show that time-regularization is effective in enhancing imaging quality.

KW - Radio-interferometric imaging

KW - Calibration

KW - Alternating forward-backward approach

M3 - Conference contribution

SN - 9781538647530

SP - 475

EP - 479

BT - 10th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2018)

PB - IEEE

ER -

Thouvenin P-A, Repetti A, Dabbech A, Wiaux Y. Time-Regularized Blind Deconvolution Approach for Radio Interferometry. In 10th IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM 2018). IEEE. 2018. p. 475-479