Near-optimal phase retrieval of sparse vectors

Afonso S. Bandeira, Dustin G. Mixon

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


In many areas of imaging science, it is difficult to measure the phase of linear measurements. As such, one often wishes to reconstruct a signal from intensity measurements, that is, perform phase retrieval. In several applications the signal in question is believed to be sparse. In this paper, we use ideas from the recently developed polarization method for phase retrieval and provide an algorithm that is guaranteed to recover a sparse signal from a number of phaseless linear measurements that scales linearly with the sparsity of the signal (up to logarithmic factors). This is particularly remarkable since it is known that a certain popular class of convex methods is not able to perform recovery unless the number of measurements scales with the square of the sparsity of the signal. This is a shorter version of a more complete publication that will appear elsewhere.

Original languageEnglish (US)
Title of host publicationWavelets and Sparsity XV
StatePublished - 2013
EventWavelets and Sparsity XV - San Diego, CA, United States
Duration: Aug 26 2013Aug 29 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


OtherWavelets and Sparsity XV
Country/TerritoryUnited States
CitySan Diego, CA


  • Angular Synchronization
  • Phase Retrieval
  • Polarization
  • Sparse Recovery

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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