• DocumentCode
    1656634
  • Title

    A wavelet-based multiple-description coding combining pairwise correlating transform with quincunx sub-sampling

  • Author

    Lu, Tailong ; Shi, Yunhui ; Kong, Dehui ; Yin, Baocai

  • Author_Institution
    Beijing Key Lab. of Multimedia & Intell. Software Technol., Beijing Univ. of Technol., Beijing
  • fYear
    2008
  • Firstpage
    1223
  • Lastpage
    1226
  • Abstract
    This paper proposes a novel and efficient two-description image coding scheme in the wavelet domain. Here, each description includes one basic description produced by pairwise correlating transform (PCT) and one enhanced description formed by quincunx sub-sampling. First, we partition the low-frequency wavelet coefficients into two groups. Then the PCT was applied between the two groups to generate two new correlated groups as two basic descriptions, which are coded and transmitted through two separate channels. Second, we can get two enhanced descriptions from the high-frequency wavelet coefficients of the highest-level decomposition by quincunx sub-sampling. And the Wavelet Domain Interpolation for tree Reconstruction (WDIR) is used to conceal coefficients loss in Wavelet-Trees when one enhanced description lost during transmission. Experimental results demonstrate that the proposed MDC scheme can achieve good coding performance.
  • Keywords
    image coding; image enhancement; image reconstruction; interpolation; trees (mathematics); wavelet transforms; high-frequency wavelet coefficients; highest-level decomposition; pairwise correlating transform; quincunx sub-sampling; tree reconstruction; two-description image coding scheme; wavelet domain interpolation; wavelet transform; wavelet-based multiple-description coding; Computer science; Educational institutions; Image coding; Image reconstruction; Interpolation; Laboratories; Propagation losses; Wavelet coefficients; Wavelet domain; Wavelet transforms; Pairwise correlating transform; multiple description coding; quincunx sub-sampling; spatial orientation tree;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2008. ICSP 2008. 9th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2178-7
  • Electronic_ISBN
    978-1-4244-2179-4
  • Type

    conf

  • DOI
    10.1109/ICOSP.2008.4697351
  • Filename
    4697351