• DocumentCode
    598197
  • Title

    Algorithms for transform selection in multiple-transform video compression

  • Author

    Xun Cai ; Lim, J.S.

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Massachusetts Inst. of Technol., Cambridge, MA, USA
  • fYear
    2012
  • fDate
    Sept. 30 2012-Oct. 3 2012
  • Firstpage
    2481
  • Lastpage
    2484
  • Abstract
    With a proper transform, an image or motion-compensated residual can be represented quite accurately with a small fraction of the transform coefficients. This is referred to as the energy compaction property. When multiple block transforms are used, selecting the best transform for each block that leads to the best energy compaction is difficult. In this paper, we develop two algorithms to solve this problem. The first algorithm, which is computationally simple, leads to a locally optimal solution. The second algorithm, which is more computationally intensive, gives a globally optimal solution. We discuss the algorithms and their performances. Two-dimensional discrete cosine transform (2-D DCT) and direction-adaptive one-dimensional discrete cosine transforms (1-D DCTs) are used to evaluate the performance of our algorithms. Results obtained are consistent with those from previous research.
  • Keywords
    data compression; discrete cosine transforms; image motion analysis; video coding; 1D DCT; 2D DCT; image-compensated residual; motion-compensated residual; multiple block transforms; multiple-transform video compression; one-dimensional discrete cosine transforms; transform selection; two-dimensional discrete cosine transform; Algorithm design and analysis; Compaction; Convergence; Discrete cosine transforms; Signal processing algorithms; Video compression; Transforms; energy compaction; iterative algorithms; optimization; video compression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2012 19th IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4673-2534-9
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2012.6467401
  • Filename
    6467401