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Proceedings Paper

Wavelet compression of medical image using tree-structured vector quantization and high-order entropy coding
Author(s): Jun Seok Song; Seung Jun Lee; HyoJoon Kim; JongHyo Kim; ChoongWoong Lee
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Paper Abstract

A tree-structured vector quantization system employing conditional arithmetic coding is introduced to encode wavelet coefficients of medical image. The proposed scheme efficiently reduces bit rate by exploiting inter- and intra- band correlation and effectively approximates the embedded scheme by utilizing sequential bit allocation results of the nested quantizers. The proposed scheme provides good bitrate-PSNR performance and subjective reconstruction quality with lower encoding complexity than the wavelet full-search vector quantization systems.

Paper Details

Date Published: 7 May 1997
PDF: 9 pages
Proc. SPIE 3031, Medical Imaging 1997: Image Display, (7 May 1997); doi: 10.1117/12.273954
Show Author Affiliations
Jun Seok Song, Seoul National Univ. (South Korea)
Seung Jun Lee, Seoul National Univ. (South Korea)
HyoJoon Kim, Seoul National Univ. (South Korea)
JongHyo Kim, Seoul National Univ. Hospital (South Korea)
ChoongWoong Lee, Seoul National Univ. (South Korea)


Published in SPIE Proceedings Vol. 3031:
Medical Imaging 1997: Image Display
Yongmin Kim, Editor(s)

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