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Computational Imaging for VLBI Image Reconstruction

Bouman, Katherine L. and Johnson, Michael D. and Zoran, Daniel and Fish, Vincent L. and Doeleman, Sheperd S. and Freeman, William T. (2016) Computational Imaging for VLBI Image Reconstruction. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE , Piscataway, NJ, pp. 913-922. ISBN 9781467388511. https://resolver.caltech.edu/CaltechAUTHORS:20190404-161219475

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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.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/cvpr.2016.105DOIArticle
https://arxiv.org/abs/1512.01413arXivDiscussion Paper
ORCID:
AuthorORCID
Bouman, Katherine L.0000-0003-0077-4367
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.
Funders:
Funding AgencyGrant Number
NSFCGV-1111415
NSF Graduate Research FellowshipUNSPECIFIED
NSFAST-1310896
NSFAST-1211539
NSFAST-1440254
Gordon and Betty Moore FoundationGBMF-3561
NASAUNSPECIFIED
Record Number:CaltechAUTHORS:20190404-161219475
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20190404-161219475
Official Citation:K. L. Bouman, M. D. Johnson, D. Zoran, V. L. Fish, S. S. Doeleman and W. T. Freeman, "Computational Imaging for VLBI Image Reconstruction," 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, 2016, pp. 913-922. doi: 10.1109/CVPR.2016.105
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:94484
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:05 Apr 2019 16:07
Last Modified:03 Oct 2019 21:04

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