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Proceedings Paper

Medical image compression using b-splines and vector quantization
Author(s): Javad Alirezaie; John A. Robinson
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Paper Abstract

A lossy image compression technique, incorporating least squares cubic spline pyramids, vector quantization, predictive coding and arithmetic coding was developed for the compression and reconstruction of Magnetic Resonance Images. Typical results of 29.76 dB Peak Signal-to-Noise ratio (PSNR) for 0.45 bits per pixel (bpp) compression, and 27.91 dB PSNR for 0.33 bpp, compare very favorably with other, recently reported, medical image compression results. Furthermore, block artifacts are absent from the recovered pictures.

Paper Details

Date Published: 16 September 1994
PDF: 9 pages
Proc. SPIE 2308, Visual Communications and Image Processing '94, (16 September 1994); doi: 10.1117/12.185908
Show Author Affiliations
Javad Alirezaie, Univ. of Waterloo (United Kingdom)
John A. Robinson, Univ. of Waterloo (United Kingdom)


Published in SPIE Proceedings Vol. 2308:
Visual Communications and Image Processing '94
Aggelos K. Katsaggelos, Editor(s)

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