Tensor optimization for optical-interferometric imaging

Anna Auŕla*, Rafael Carrillo, Jean-Philippe Thiran, Yves Wiaux

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
90 Downloads (Pure)


Image recovery in optical interferometry is an ill-posed non-linear inverse problem arising from incomplete power spectrum and bispectrum measurements. We reformulate this nonlinear problem as a linear problem for the supersymmetric rank-1 order-3 tensor formed by the tensor product of the vector representing the image under scrutiny with itself. On one hand, we propose a linear convex approach for tensor recovery with built-in supersymmetry, and regularizing the inverse problem through a nuclear norm relaxation of a low-rank constraint. On the other hand, we also study a non-linear non-convex approach with a built-in rank-1 constraint but where supersymmetry is relaxed, formulating the problem for the tensor product of three vectors. In this second approach, only linear convex minimization subproblems are, however, solved, alternately and iteratively for the three vectors. We provide a comparative analysis of these two novel approaches through numerical simulations on small-size images. © 2013 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society.

Original languageEnglish
Pages (from-to)2083-2091
Number of pages9
JournalMonthly Notices of the Royal Astronomical Society
Issue number3
Publication statusPublished - 21 Jan 2014


  • Image processing-techniques
  • Interferometric
  • Techniques

ASJC Scopus subject areas

  • Space and Planetary Science
  • Astronomy and Astrophysics


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