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SNR and temporal scalable coding of 3-D mesh sequences using singular value decomposition

  • Jun Hee Heu
  • , Chang-Su Kim*
  • , Sang Uk Lee
  • *Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    Abstract

    A signal-to-noise ratio (SNR) and temporal scalable coding algorithm for 3-D mesh sequences using singular value decomposition (SVD) is proposed in this work. The proposed algorithm employs SVD to represent a mesh sequence with a small number of basis vectors, and encodes those basis vectors with a bit plane coder. We analytically derive the contribution of each bit plane to the reconstructed mesh quality, and transmit the bit planes in the decreasing order of their amounts of contribution. As the decoder receives more bit planes, it reconstructs higher quality mesh sequences progressively. Moreover, we develop a temporal prediction mode to improve the rate-distortion (R-D) performance further, which also supports temporal scalability. Simulation results demonstrate that the proposed algorithm yields significantly better R-D performance than conventional SVD-based coders.

    Original languageEnglish
    Pages (from-to)439-449
    Number of pages11
    JournalJournal of Visual Communication and Image Representation
    Volume20
    Issue number7
    DOIs
    Publication statusPublished - 2009 Oct

    Bibliographical note

    Funding Information:
    The work of J.-H. Heu and S.-U. Lee was supported by the Ministry of Knowledge Economy (MKE), Korea, under the ITRC support program supervised by the IITA (Grant No. IITA-2009-C1090-0902-0018). The work of C.-S. Kim was supported partly by the Korea Research Foundation Grant funded by the Korean Government (KRF-2008-331-D00420) and partly by the MKE, Korea, under the ITRC support program supervised by the IITA (Grant No. IITA-2009-C1090-0902-0017).

    Keywords

    • 3-D mesh coding
    • Bit plane coding
    • Mesh sequence
    • Rate-distortion optimization
    • SNR scalability
    • Scalable coding
    • Singular value decomposition
    • Temporal scalability

    ASJC Scopus subject areas

    • Signal Processing
    • Media Technology
    • Computer Vision and Pattern Recognition
    • Electrical and Electronic Engineering

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