Skip to main content

Progressive Lower Trees of Wavelet Coefficients: Efficient Spatial and SNR Scalable Coding of 3D Models

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3767))

Abstract

We perform an in-depth analysis of current state-of-the-art waveletbased 3D model coding techniques and then present a new one that outperforms them in terms of compression efficiency and, more importantly, provides full spatial and SNR scalability: PLTW (Progressive Lower Tree Wavelet) coding. As all SNR scalable bit-streams, ours can be used in heterogeneous networks with a wide range of terminals, both in terms of processing power and bandwidth. But because of being spatially scalable, the PLTW bit-stream does not impose on the less powerful terminals the need of building detail trees as deep as required by the maximum LOD, because the wavelet coefficients are sent on a per-LOD basis, thus achieving a “local” SNR scalability within a “global” spatial scalability. In particular, we show that our technique provides a substantial advantage over the only similar one in a current ISO standard (MPEG-4), and thus suggest that PLTW be considered for its future versions.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aspert, N., Santa Cruz, D., Ebrahimi, T.: MESH: Measuring Errors between Surfaces using the Hausdorff Distance. In: Proceedings of the IEEE International Conference on Multimedia and Expo, August 2002, pp. 705–708 (2002)

    Google Scholar 

  2. Khodakovsky, A., Schröder, P., Sweldens, W.: Progressive Geometry Compression. In: Proceedings of the ACM SIGGRAPH Conference, July 2000, pp. 271–278 (2000)

    Google Scholar 

  3. Morán, F., García, N.: Comparison of Wavelet-Based Three-Dimensional Model Coding Techniques. IEEE Transactions on Circuits and Systems for Video Technology 14(7), 937–949 (2004)

    Article  Google Scholar 

  4. MPEG: ISO/IEC 14496 (MPEG-4) Part 16: Animation Framework eXtension (AFX), ISO/IEC (International Standard status) (April 2003)

    Google Scholar 

  5. Oliver, J., Malumbres, M.P.: Fast and Efficient Spatial Scalable Image Compression using Wavelet Lower Trees. In: Proceedings of the IEEE Data Compression Conference, March 2003, pp. 133–142 (2003)

    Google Scholar 

  6. Said, A., Pearlman, A.: A New, Fast and Efficient Image Codec Based on Set Partitioning in Hierarchical Trees. IEEE Transactions on Circuits and Systems for Video Technology 6(3), 243–250 (1996)

    Article  Google Scholar 

  7. Taubman, D.: High Performance Scalable Image Compression with EBCOT. IEEE Transactions on Image Processing 9(7), 1158–1170 (2000)

    Article  Google Scholar 

  8. Witten, I.H., Neal, R.M., Cleary, J.G.: Arithmetic Coding for Data Compression. Communications of the ACM 30(6), 520–540 (1987)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Avilés, M., Morán, F., García, N. (2005). Progressive Lower Trees of Wavelet Coefficients: Efficient Spatial and SNR Scalable Coding of 3D Models. In: Ho, YS., Kim, H.J. (eds) Advances in Multimedia Information Processing - PCM 2005. PCM 2005. Lecture Notes in Computer Science, vol 3767. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11581772_6

Download citation

  • DOI: https://doi.org/10.1007/11581772_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30027-4

  • Online ISBN: 978-3-540-32130-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics