Distance retrieval from unknown view tomography of 2D point sources

Mona Zehni, Shuai Huang, Ivan Dokmanić, Zhizhen Zhao

Research output: Contribution to journalConference articlepeer-review


In this paper, we study a 2D tomography problem with random and unknown projection angles for a point source model. Specifically, we target recovering geometry information, i.e. the radial and pairwise distances of the underlying point source model. For this purpose, we introduce a set of rotation-invariant features that are estimated from the projection data. We further show these features are functions of the radial and pairwise distances of the point source model. By extracting the distances from the features, we gain insight into the geometry of the unknown point source model. This geometry information can be used later on to reconstruct the point source model. The simulation results verify the robustness of our method in presence of noise and errors in the estimation of the features.

Original languageEnglish (US)
Article numberCOIMG-134
Pages (from-to)134-1-134-5
JournalIS and T International Symposium on Electronic Imaging Science and Technology
Issue number13
StatePublished - Jan 13 2019
Event17th Computational Imaging Conference, CI 2019 - Burlingame, United States
Duration: Jan 13 2019Jan 17 2019


  • cryo-electron microscopy
  • point source localization
  • rotation invariant features
  • unassigned distance geometry problem

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Software
  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics


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