Skip to main content

GPU-Supported Image Compression for Remote Visualization – Realization and Benchmarking

  • Conference paper
Advances in Visual Computing (ISVC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5358))

Included in the following conference series:

Abstract

In this paper we introduce a novel GPU-supported JPEG image compression technique with a focus on its application for remote visualization purposes. Fast and high quality compression techniques are very important for the remote visualization of interactive simulations and Virtual reality applications (IS/VR) on hybrid clusters. Thus the main goals of the design and implementation of this compression technique were low compression times and nearly no visible quality loss, while achieving compression rates that allow for 30+ Frames per second over 10 MBit/s networks. To analyze the potential of the technique and further development needs and to compare it to existing methods, several benchmarks are conducted and described in this paper. Additionally a quality assessment is performed to allow statements about the achievable quality of the lossy image compression. The results show that using the GPU not only for rendering but also for image compression is a promising approach for interactive remote rendering.

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

Access this chapter

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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Lietsch, S., Zabel, H., Berssenbruegge, J.: Computational Steering of Interactive and Distributed Virtual Reality Applications. In: ASME CIE 2007: Proceedings of the 27th ASME Computers and Information in Engineering Conference, ASME (2007)

    Google Scholar 

  2. Lietsch, S., Marquardt, O.: A CUDA-Supported Approach to Remote Rendering. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Paragios, N., Tanveer, S.-M., Ju, T., Liu, Z., Coquillart, S., Cruz-Neira, C., Müller, T., Malzbender, T. (eds.) ISVC 2007, Part I. LNCS, vol. 4841, pp. 724–733. Springer, Heidelberg (2007)

    Chapter  Google Scholar 

  3. VirtualGL: The VirtualGL Project (2007), http://www.virtualgl.org/

  4. Independent JPEG Group: libjpeg (Open Source JPEG library) (2008), http://www.ijg.org

  5. VirtualGL: TurboJPEG 1.10 - Intel IPP accelerated JPEG compression (2008), http://www.sourceforge.net /project/showfiles.php?group_id=117509&package_id=166100

  6. Intel: Intel Integrated Performance Primitives 5.3 (2008), http://www.intel.com /cd/software/products/asmo-na/eng/302910.htm

  7. NVIDIA: NVIDIA CUDA - Compute Unified Device Architecture (2008), http://www.nvidia.com/object/cuda_home.html

  8. Pennebaker, W.B., Mitchell, J.L.: JPEG Still Image Data Compression Standard. Kluwer Academic Publishers, Norwell (1992)

    Google Scholar 

  9. Arai, Y., Agui, T., Nakajima, M.: A Fast DCT-SQ Scheme for Images. Transactions of IEICE E71, 1095–1097 (1988)

    Google Scholar 

  10. Howard, P.G., Vitter, J.S.: Parallel lossless image compression using Huffman and arithmetic coding. Information Processing Letters 59, 65–73 (1996)

    Article  MATH  Google Scholar 

  11. Crochemore, M., Wojciech, W.R.: Jewels of stringology. World Scientific Publishing Co. Inc., River Edge (2003)

    MATH  Google Scholar 

  12. Wang, Z., Bovik, A., Sheikh, H., Simoncelli, E.: Image Quality Assessment: From Error Visibility to Structural Similarity. IEEE Transactions on Image Processing 13, 600–612 (2004)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lietsch, S., Lensing, P.H. (2008). GPU-Supported Image Compression for Remote Visualization – Realization and Benchmarking. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89639-5_63

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-89639-5_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-89638-8

  • Online ISBN: 978-3-540-89639-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics