• DocumentCode
    3432195
  • Title

    Bi-level image compression using adaptive tree model

  • Author

    Nguyen-Phi, Khanh ; Weinrichter, Hans

  • Author_Institution
    Wien Univ., Austria
  • fYear
    1997
  • fDate
    25-27 Mar 1997
  • Firstpage
    458
  • Abstract
    Summary form only given. State-of-the-art methods for bi-level image compression rely on two processes of modelling and coding. The modelling process determines the context of the coded pixel based on its adjacent pixels and using the information of the context to predict the probability of the coded pixel being 0 or 1. The coding process will actually code the pixel based on the prediction. Because the source is finite, a bigger template (more adjacent pixels) doesn´t always lead to a better result, which is known as “context dilution” phenomenon. The authors present a new method called adaptive tree modelling for preventing the context dilution. They discussed this method by considering a pruned binary tree. They have implemented the proposed method in software
  • Keywords
    adaptive codes; image coding; source coding; tree data structures; adaptive tree model; adjacent pixels; bi-level image compression; coded pixel; coding process; context dilution; modelling process; prediction; pruned binary tree; template; Binary trees; Context modeling; Image coding; Predictive models; Testing; Tree data structures;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Compression Conference, 1997. DCC '97. Proceedings
  • Conference_Location
    Snowbird, UT
  • ISSN
    1068-0314
  • Print_ISBN
    0-8186-7761-9
  • Type

    conf

  • DOI
    10.1109/DCC.1997.582122
  • Filename
    582122