• DocumentCode
    3051716
  • Title

    Successive coefficient refinement for embedded lossless image compression

  • Author

    Creusere, Charles D.

  • Author_Institution
    Weapons Div., Naval Air Warfare Center, China Lake, CA, USA
  • fYear
    1998
  • fDate
    30 Mar-1 Apr 1998
  • Firstpage
    539
  • Abstract
    Summary form only given. We consider here a new approach to successive coefficient refinement which speeds up embedded image compression and decompression. Rather than sending the binary refinement symbol typical of existing embedded coders, our algorithm uses a ternary refinement symbol, allowing the encoder to tell the decoder when its current approximation of a given wavelet coefficient is exact. Thus, both encoder and decoder operate faster because they process fewer refinement symbols, yet the fundamental structure of the refinement process remains unchanged, i.e. it still represents a binary subdivision of the uncertainty interval. To implement a complete encoder, we combine the proposed refinement process with Shapiro´s embedded zerotree wavelet (EZW) algorithm. Results for lossless compression are shown. Without optimization, the speed increase is between 5 and 12%; with optimization, it is between 9 and 15%
  • Keywords
    data compression; image coding; transform coding; wavelet transforms; EZW algorithm; binary subdivision; decoder; embedded lossless image compression; embedded zerotree wavelet algorithm; encoder; image decompression; optimization; successive coefficient refinement; ternary refinement symbol; uncertainty interval; wavelet coefficient; Approximation algorithms; Bit rate; Decoding; Image coding; Lakes; PSNR; Propagation losses; Uncertainty; Wavelet coefficients; Weapons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Compression Conference, 1998. DCC '98. Proceedings
  • Conference_Location
    Snowbird, UT
  • ISSN
    1068-0314
  • Print_ISBN
    0-8186-8406-2
  • Type

    conf

  • DOI
    10.1109/DCC.1998.672262
  • Filename
    672262