Mathematical Programming Computation, Volume 8, Issue 3, September 2016
Phase retrieval for imaging problems
Fajwel Fogel, Irène Waldspurger, Alexandre D’Aspremont
We study convex relaxation algorithms for phase retrieval on imaging problems. We show that exploiting structural assumptions on the signal and the observations, such as sparsity, smoothness or positivity, can significantly speed-up convergence and improve recovery performance. We detail numerical results in molecular imaging experiments simulated using data from the Protein Data Bank.
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