Sparsity in tensor optimization for optical-interferometric imaging

Anna Auria, Rafael E. Carrillo, Jean Philippe Thiran, Yves Wiaux

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Image recovery in optical interferometry is an ill-posed nonlinear inverse problem arising from incomplete power spectrum and bispectrum measurements. We review our previous work, which reformulates this nonlinear problem in the framework of tensor recovery and studies two different approaches to solve it: one is nonlinear and nonconvex while the other is linear and convex. We extend the linear convex procedure to account for signal sparsity and we also present numerical simulations that show the improvement in the quality of reconstruction of sparse images when including a sparsity prior.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
PublisherIEEE
Pages6026-6030
Number of pages5
ISBN (Print)978-1-4799-5751-4
DOIs
Publication statusPublished - 2015
Event21st IEEE International Conference on Image Processing 2014 - Paris, France
Duration: 27 Oct 201430 Oct 2014

Conference

Conference21st IEEE International Conference on Image Processing 2014
Abbreviated titleICIP 2014
CountryFrance
CityParis
Period27/10/1430/10/14

Keywords

  • interferometric imaging
  • optical interferometry
  • phase retrieval
  • tensor optimization

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Auria, A., Carrillo, R. E., Thiran, J. P., & Wiaux, Y. (2015). Sparsity in tensor optimization for optical-interferometric imaging. In 2014 IEEE International Conference on Image Processing, ICIP 2014 (pp. 6026-6030). [7026216] IEEE. https://doi.org/10.1109/ICIP.2014.7026216