• DocumentCode
    3295678
  • Title

    Methodologies for the adaptive compression of video sequences

  • Author

    Cenedese, Angelo ; Marcon, Riccardo

  • Author_Institution
    Dept. of Eng. & Manage., Univ. of Padova, Vicenza, Italy
  • fYear
    2009
  • fDate
    15-18 Dec. 2009
  • Firstpage
    794
  • Lastpage
    799
  • Abstract
    In this work, a procedure for the video compression and transmission is presented, based on a Singular Value Decomposition approach, whose controls are obtained as the output of a constrained optimization problem that refers to the compression ratio as the optimization functional and an image quality index as the performance constraint. The tools of estimation theory allow to obtain a polynomial approximation of these indexes in a static fashion via least square technique, and adaptively, with the concurrent estimation of both the order of the polynomial functions and the salient function parameters through the use of Kalman Filters. The implementation of the whole system and some simulations of real video sequences are presented to validate and assess the proposed procedure.
  • Keywords
    Kalman filters; data compression; estimation theory; least squares approximations; optimisation; polynomial approximation; singular value decomposition; video coding; Kalman filter; compression ratio; constrained optimization problem; estimation theory; image quality index; least square technique; optimization functional; performance constraint; polynomial approximation; polynomial function parameter; salient function parameter; singular value decomposition; video sequences adaptive compression; Computational modeling; Constraint optimization; Decoding; Image coding; Image quality; Least squares approximation; Polynomials; Singular value decomposition; Video compression; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
  • Conference_Location
    Shanghai
  • ISSN
    0191-2216
  • Print_ISBN
    978-1-4244-3871-6
  • Electronic_ISBN
    0191-2216
  • Type

    conf

  • DOI
    10.1109/CDC.2009.5399665
  • Filename
    5399665