Scalable low complexity image coder for remote volume visualization

Hariharan G. Lalgudi, Michael W. Marcellin, Ali Bilgin, Mariappan S. Nadar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


Remote visualization of volumetric data has gained importance over the past few years in order to realize the full potential of tele-radiology. Volume rendering is a computationally intensive process, often requiring hardware acceleration to achieve real time visualization. Hence a remote visualization model that is well-suited for high speed networks would be to transmit rendered images from the server (with dedicated hardware) based on view point requests from clients. In this regard, a compression scheme for the rendered images is vital for efficient utilization of the server-client bandwidth. Also, the complexity of the decompressor should be considered so that a low end client workstation can decode images at the desired frame rate. We present a scalable low complexity image coder that has good compression efficiency and high throughput.

Original languageEnglish (US)
Title of host publicationApplications of Digital Image Processing XXXI
StatePublished - 2008
EventApplications of Digital Image Processing XXXI - San Diego, CA, United States
Duration: Aug 11 2008Aug 14 2008

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


OtherApplications of Digital Image Processing XXXI
Country/TerritoryUnited States
CitySan Diego, CA


  • Image compression
  • Remote visualization

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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