Wavelet compression of medical images with set partitioning in hierarchical trees

Armando Manduca, Amir Said

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

19 Scopus citations

Abstract

Wavelet-based image compression is proving to be a very effective technique for medical images, giving significantly better results than the JPEG algorithm. A novel scheme for encoding wavelet coefficients, termed set partitioning in hierarchical trees, has recently been proposed and yields significantly better compression than more standard methods. We report the results of experiments comparing such coding to more conventional wavelet compression and to JPEG compression on several types of medical images.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsYongmin Kim
Pages192-200
Number of pages9
Volume2707
StatePublished - 1996
EventMedical Imaging 1996: Image Display - Newport Beach, CA, USA
Duration: Feb 11 1996Feb 13 1996

Other

OtherMedical Imaging 1996: Image Display
CityNewport Beach, CA, USA
Period2/11/962/13/96

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ASJC Scopus subject areas

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

Cite this

Manduca, A., & Said, A. (1996). Wavelet compression of medical images with set partitioning in hierarchical trees. In Y. Kim (Ed.), Proceedings of SPIE - The International Society for Optical Engineering (Vol. 2707, pp. 192-200)