Progressive compression of point texture images

In Wook Song, Chang Su Kim, Sang Uk Lee

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)


In this paper, we develop a tree-structured predictive partial matching (PPM) scheme for progressive compression of Point Texture images. By incorporating PPM with tree-structured coding, the proposed algorithm can compress 3D depth information progressively into a single bitstream. Also, the proposed algorithm compresses color information using a differential pulse coding modulation (DPCM) coder and interweaves the compressed depth and color information efficiently. Thus, the decoder can reconstruct 3D models from the coarsest resolution to the highest resolution from a single bitstream. Simulation results demonstrate that the proposed algorithm provides much better compression performance than a universal Lempel-Ziv coder, WinZip.

Original languageEnglish
Pages (from-to)1159-1168
Number of pages10
JournalProceedings of SPIE - The International Society for Optical Engineering
Issue numberPART 2
Publication statusPublished - 2004
Externally publishedYes
EventVisual Communications and Image Processing 2004 - San Jose, CA, United States
Duration: 2004 Jan 202004 Jan 22


  • 3D compression
  • Depth image based rendering
  • Layered depth images
  • Octree structure
  • Point-Texture
  • Progressive compression

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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