Sparsity in tensor optimization for optical-interferometric imaging

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 so...

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Bibliographic Details
Main Authors: Auria, Anna, Carrillo, Rafael E., Thiran, Jean-Philippe, Wiaux, Yves
Format: Conference Proceeding
Language:English
Subjects:
Image reconstruction
interferometric imaging
Minimization
Optical imaging
Optical interferometry
phase retrieval
Signal to noise ratio
Tensile stress
tensor optimization
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Summary: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.
ISSN:1522-4880
2381-8549
DOI:10.1109/ICIP.2014.7026216