Medical image compression with wavelet/subband coding

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations

Abstract

Wavelet transforms have recently gained wide application in many areas of signal and image processing and are particularly well-suited to efficiently encoding real-world images. The localized nature of the wavelet transform also lends itself to allowing the user to specify areas of interest that can be preserved with maximum fidelity while the rest of the image, which provides context, is compressed. We present examples of wavelet-based compression on a variety of medical images, and comparisons with JPEG compressions. We also discuss the improvement gained by true 3-D compression of a 3-D image, and issues in the treatment of human visual system response, and extensions of the current approach to still more efficient compression schemes.

Original languageEnglish (US)
Title of host publicationArtificial Neural Networks in Engineering - Proceedings (ANNIE'94)
Place of PublicationNew York, NY, United States
PublisherASME
Pages645-650
Number of pages6
Volume4
StatePublished - 1994
EventProceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94) - St. Louis, MO, USA
Duration: Nov 13 1994Nov 16 1994

Other

OtherProceedings of the Artificial Neural Networks in Engineering Conference (ANNIE'94)
CitySt. Louis, MO, USA
Period11/13/9411/16/94

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Manduca, A. (1994). Medical image compression with wavelet/subband coding. In Artificial Neural Networks in Engineering - Proceedings (ANNIE'94) (Vol. 4, pp. 645-650). ASME.