Compressed Sensing for Aperture Synthesis Imaging
The theory of compressed sensing has a natural application in interferometric aperture synthesis. As in many real-world applications, however, the assumption of random sampling, which is elementary to many propositions of this theory, is not met. Instead, the induced sampling patterns exhibit a large degree of regularity. In this paper, we statistically quantify the effects of this kind of regularity for the problem of radio interferometry where astronomical images are sparsely sampled in the frequency domain. Based on the favorable results of our statistical evaluation, we present a practical method for interferometric image reconstruction that is evaluated on observational data from the Very Large Array (VLA) telescope.
Author(s): | Stephan Wenger, Soheil Darabi, Pradeep Sen, Karl-Heinz Glassmeier, Marcus Magnor |
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Published: | September 2010 |
Type: | Article in conference proceedings |
Book: | Proc. IEEE International Conference on Image Processing (ICIP) |
Presented at: | IEEE International Conference on Image Processing (ICIP) |
Project(s): | Radio Astronomy Synthesis Imaging |
@inproceedings{wenger2010compressed, title = {Compressed Sensing for Aperture Synthesis Imaging}, author = {Wenger, Stephan and Darabi, Soheil and Sen, Pradeep and Glassmeier, Karl-Heinz and Magnor, Marcus}, booktitle = {Proc. {IEEE} International Conference on Image Processing ({ICIP})}, pages = {1381--1384}, month = {Sep}, year = {2010} }
Authors
Stephan Wenger
Fmr. Senior ResearcherSoheil Darabi
ExternalPradeep Sen
ExternalKarl-Heinz Glassmeier
ExternalMarcus Magnor
Director, Chair