A Fourier dimensionality reduction model for big data interferometric imaging

@article{Kartik2017AFD,
  title={A Fourier dimensionality reduction model for big data interferometric imaging},
  author={S. Vijay Kartik and Rafael E. Carrillo and Jean-Philippe Thiran and Yves Wiaux},
  journal={Monthly Notices of the Royal Astronomical Society},
  year={2017},
  volume={468},
  pages={2382-2400}
}
Data dimensionality reduction in radio interferometry can provide savings of computational resources for image reconstruction through reduced memory footprints and lighter computations per iteration, which is important for the scalability of imaging methods to the big data setting of the next-generation telescopes. This article sheds new light on dimensionality reduction from the perspective of compressed sensing theory and studies its interplay with imaging algorithms designed in the context… 

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