• DocumentCode
    1661527
  • Title

    Optical flow for compressive sensing video reconstruction

  • Author

    Braun, Hans-Georg ; Turaga, Pavan ; Tepedelenlioglu, Cihan ; Spanias, A.

  • Author_Institution
    SenSIP Center & Ind. Consortium, Arizona State Univ., Tempe, AZ, USA
  • fYear
    2013
  • Firstpage
    2267
  • Lastpage
    2271
  • Abstract
    Although considerable effort has been devoted to the problem of reconstructing compressively sensed video, no existing algorithm achieves results comparable to commonly available video compression methods such as H.264. One possible avenue for improving compressively sensed video reconstruction is the use of optical flow information. Current efforts reported in the literature have not fully utilized optical flow information, instead focusing on limited cases such as stationary backgrounds with sparse foreground motion. In this paper, a reconstruction method is presented which fully utilizes optical flow information to increase the quality of reconstruction. The special cases of known image motion and constant global image motion are presented, and the performance of the algorithm on existing datasets is evaluated.
  • Keywords
    compressed sensing; image reconstruction; image sequences; video signal processing; compressive sensing; global image motion; optical flow; video reconstruction; Adaptive optics; Image coding; Image reconstruction; Optical imaging; Optical sensors; Optical variables measurement; Compressive Sensing; Image Reconstruction; Motion Estimation; Optical Flow;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
  • Conference_Location
    Vancouver, BC
  • ISSN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2013.6638058
  • Filename
    6638058