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

Jun Hee Heu, Chang-Su Kim, Sang Uk Lee

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)


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
Issue number7
Publication statusPublished - 2009 Oct


  • 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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