High-resolution imaging using a translating coded aperture

Abhijit Mahalanobis, Richard Shilling, Robert Muise, Mark Neifeld

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


It is well known that a translating mask can optically encode low-resolution measurements from which higher resolution images can be computationally reconstructed. We experimentally demonstrate that this principle can be used to achieve substantial increase in image resolution compared to the size of the focal plane array (FPA). Specifically, we describe a scalable architecture with a translating mask (also referred to as a coded aperture) that achieves eightfold resolution improvement (or 64:1 increase in the number of pixels compared to the number of focal plane detector elements). The imaging architecture is described in terms of general design parameters (such as field of view and angular resolution, dimensions of the mask, and the detector and FPA sizes), and some of the underlying design trades are discussed. Experiments conducted with different mask patterns and reconstruction algorithms illustrate how these parameters affect the resolution of the reconstructed image. Initial experimental results also demonstrate that the architecture can directly support task-specific information sensing for detection and tracking, and that moving objects can be reconstructed separately from the stationary background using motion priors.

Original languageEnglish (US)
Article number084106
JournalOptical Engineering
Issue number8
StatePublished - Aug 1 2017


  • coded aperture
  • computational imaging
  • digital super resolution
  • task specific imaging

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Engineering(all)


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