Spatio-temporal sampling for video

Mohan Shankar, Nikos P. Pitsianis, David Brady

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

2 Scopus citations


With this work we propose spatio-temporal sampling strategies for video using a lenslet array computational imaging system and explore the opportunities and challenges in the design of compressive video sensors and corresponding processing algorithms. The redundancies in video streams are exploited by (a) sampling the sub-apertures of a multichannel (TOMBO) camera, and (b) by the computational reconstruction to achieve low power and low complexity video sensors. A spatial and a spatio-temporal sampling strategy are considered, taking into account the feasibility for implementation in the focal-plane readout hardware. The algorithms used to reconstruct the video frames from measurements are also presented.

Original languageEnglish (US)
Title of host publicationImage Reconstruction from Incomplete Data V
StatePublished - 2008
Externally publishedYes
EventImage Reconstruction from Incomplete Data V - San Diego, CA, United States
Duration: Aug 11 2008Aug 12 2008

Publication series

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


ConferenceImage Reconstruction from Incomplete Data V
Country/TerritoryUnited States
CitySan Diego, CA


  • Coded aperture imager
  • Compressive sampling

ASJC Scopus subject areas

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


Dive into the research topics of 'Spatio-temporal sampling for video'. Together they form a unique fingerprint.

Cite this