Compressed Sensing for Aperture Synthesis Imaging Stephan Wenger, Soheil Darabi, Pradeep Sen, Karl-Heinz Glassmeier, Marcus Magnor

Stephan Wenger, Soheil Darabi, Pradeep Sen, Karl-Heinz Glassmeier, and Marcus Magnor: "Compressed Sensing for Aperture Synthesis Imaging", in Proc. IEEE International Conference on Image Processing (ICIP), pp. 1381–1384, September 2010. Part of project "Astrographics". [pdf] [bib]

Abstract

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.

TU Braunschweig - Fakultät für Mathematik und Informatik - Computer Graphics - Publications - Compressed Sensing for Aperture Synthesis Imaging