Adaptive temporal compressive sensing for video

Xin Yuan, Jianbo Yang, Patrick Llull, Xuejun Liao, Guillermo Sapiro, David J. Brady, Lawrence Carin

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

34 Scopus citations

Abstract

This paper introduces the concept of adaptive temporal compressive sensing (CS) for video. We propose a CS algorithm to adapt the compression ratio based on the scene's temporal complexity, computed from the compressed data, without compromising the quality of the reconstructed video. The temporal adaptivity is manifested by manipulating the integration time of the camera, opening the possibility to realtime implementation. The proposed algorithm is a generalized temporal CS approach that can be incorporated with a diverse set of existing hardware systems.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
PublisherIEEE Computer Society
Pages14-18
Number of pages5
ISBN (Print)9781479923410
DOIs
StatePublished - 2013
Externally publishedYes
Event2013 20th IEEE International Conference on Image Processing, ICIP 2013 - Melbourne, VIC, Australia
Duration: Sep 15 2013Sep 18 2013

Publication series

Name2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

Conference

Conference2013 20th IEEE International Conference on Image Processing, ICIP 2013
Country/TerritoryAustralia
CityMelbourne, VIC
Period9/15/139/18/13

Keywords

  • Video compressive sensing
  • adaptive temporal compressive sensing
  • real-time implementation
  • temporal compressive sensing ratio design
  • temporal superresolution

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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