Computational Imaging for VLBI Image Reconstruction
Abstract
Very long baseline interferometry (VLBI) is a technique for imaging celestial radio emissions by simultaneously observing a source from telescopes distributed across Earth. The challenges in reconstructing images from fine angular resolution VLBI data are immense. The data is extremely sparse and noisy, thus requiring statistical image models such as those designed in the computer vision community. In this paper we present a novel Bayesian approach for VLBI image reconstruction. While other methods often require careful tuning and parameter selection for different types of data, our method (CHIRP) produces good results under different settings such as low SNR or extended emission. The success of our method is demonstrated on realistic synthetic experiments as well as publicly available real data. We present this problem in a way that is accessible to members of the community, and provide a dataset website (vlbiimaging.csail.mit.edu) that facilitates controlled comparisons across algorithms.
Additional Information
© 2016 IEEE. We would like to thank Andrew Chael, Katherine Rosenfeld, and Lindy Blackburn for all of their helpful discussions and feedback. This work was partially supported by NSF CGV-1111415. Katherine Bouman was partially supported by an NSF Graduate Fellowship. We also thank the National Science Foundation (AST-1310896, AST-1211539, and AST-1440254) and the Gordon and Betty Moore Foundation (GBMF-3561) for financial support of this work. This study makes use of 43 GHz VLBA data from the VLBA-BU Blazar Monitoring Program (VLBA-BU-BLAZAR; http://www.bu.edu/blazars/VLBAproject.html), funded by NASA through the Fermi Guest Investigator Program. The VLBA is an instrument of the National Radio Astronomy Observatory. The National Radio Astronomy Observatory is a facility of the National Science Foundation operated by Associated Universities, Inc.Attached Files
Accepted Version - 1512.01413.pdf
Files
| Name | Size | Download all |
|---|---|---|
|
md5:7ed2c40fc31fa7ea76ade337876b37ea
|
1.5 MB | Preview Download |
Additional details
- Eprint ID
- 94484
- Resolver ID
- CaltechAUTHORS:20190404-161219475
- CGV-1111415
- NSF
- NSF Graduate Research Fellowship
- AST-1310896
- NSF
- AST-1211539
- NSF
- AST-1440254
- NSF
- GBMF-3561
- Gordon and Betty Moore Foundation
- NASA
- Created
-
2019-04-05Created from EPrint's datestamp field
- Updated
-
2021-11-16Created from EPrint's last_modified field