• DocumentCode
    1149451
  • Title

    Adaptive entropy-constrained residual vector quantization

  • Author

    Kossentini, Faouzi ; Smith, Mark J T

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA
  • Volume
    1
  • Issue
    8
  • fYear
    1994
  • Firstpage
    121
  • Lastpage
    123
  • Abstract
    Entropy-constrained residual vector quantization (EC-RVQ) is a relatively new VQ method that was shown to be capable of excellent rate-distortion performance. The paper investigates the incorporation of adaptivity into the EC-RVQ framework for application to image coding. Experimental results show that the dynamic nature of the implementation leads to a noticeable improvement in coding quality as well as improved robustness.<>
  • Keywords
    adaptive systems; entropy; image coding; vector quantisation; EC-RVQ; VQ method; adaptive entropy-constrained residual vector quantization; coding quality; image coding; rate-distortion performance; robustness; Algorithm design and analysis; Bit rate; Design optimization; Entropy; Image coding; Iterative algorithms; Lagrangian functions; Rate-distortion; Robustness; Vector quantization;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/97.311814
  • Filename
    311814
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1149451